TrustRadius
https://media.trustradius.com/product-logos/6C/b9/XR09NAFJA7EB.JPEGGrateful for this software!We use Arm Treasure Data as our ETL hub. We extract data using its connectors to several sources, such as Salesforce. We transform data using Treasure's query tools and also use it to build scheduled workflows. And we ultimately load ready to use tables into visualization tools such as Tableau. This process allows us to combine and centralize our data into a format to best make use of it to uncover business insights and create reporting for accountability and tracking purposes.,Building Workflows is easy using Treasure's interface. You can run many jobs in parallel or in sequence and those jobs can run at scheduled times and create the right tables and data loads you need. Being able to write queries (in Presto or Hive) using the all the data sources you have brought in to either create tables, run a query, or export data to a variety of sources is seamless and intuitive. Extracting data from a variety of sources is fairly easy. Very responsive and helpful customer service who you can reach easily by Chat.,Pricing is a bit of a black box. We are currently priced on split hour usage and some spikes come out of nowhere and leave us seeking answers (and sometimes finding unsatisfactory ones). Some jobs will fail, causing workflows to be interrupted due to a product change or a one-time product related issue. We usually contact Support in these cases, and while they are incredibly responsive and helpful, it would be great to have more proactive communication. Treasure's UI leaves us wanting more in terms of organization and controls, especially as we scale and grow the number of data sources, queries, and workflows.,8,We have built and supported our source of truth data tables using Treasure. This forms the foundation of our decision making. Most of our Tableau data sources are created using a Treasure Data export which is executed by workflows on a daily basis which allows us to have visibility into day to day performance and communicate them to a wide variety of roles. We load custom data into our Salesforce instance which allows us to trigger certain workflows and build accountability - i.e. a "Sale" will only count once a certain product driven event occurs which comes from data we pipe into Treasure and then into Salesforce.,We have without a doubt become more data driven due to Treasure Data. Our Sales and Marketing teams rely on Tableau reports and visualizations to monitor and make decisions on their business. We have been able to get to this point by being able to create the source of truth data sources and putting them in places we can best manipulate them - all of which is enabled by Treasure.,Loading custom data into Salesforce Objects Automating Sales commissions by creating the commission logic in Treasure Queries which create tables which we then pipe into Tableau Keeping our data up-to-date by having workflows which extract the data, transform it with queries, and load the result tables into a wide variety of sources.,,Tableau Online, PostgreSQL, SlackTreasure Data works for small companies!We utilize Treasure Data as a way to bring in data from SFDC and translate it in a useful way for Tableau. It is a workflow management tool, SQL tool, and exporter. SFDC reporting has limitations especially for cohort analysis, so we need to manipulate the data outside of SFDC. TD provides a great way to import and export data we need into SFDC. The entire company utilizes the data from SFDC. Only select analysts are able to have access to Treasure Data itself. These analysts do not have experience in managing data and data sources, so Treasure Data has been a helpful tool that assists with the gap.,Importing data from Salesforce and other sources - with no or little background in data sources, Treasure Data has been useful with assisting the gap. Exporting data into Salesforce and Tableau is very simple to set up and can be easily scheduled. Support from Treasure Data is a live chat and has been VERY helpful with assisting a lot of the little issues that we run into.,There are often bugs when they update the source connections. However, they are diligent and have been correcting the issues in a timely matter. There are often slow downs with our workflows and increase in Presto usage hours that aren't explainable. We don't change the queries, but we see slow downs over time.,8,Positive: Workflows and scheduling have provided fewer crashes and orderly updates for the company that heavily depend on reporting. Negative: Workflows are limited. Once it breaks, it cannot skip tasks. It fails and a warning email is sent out.,The company is/was heavily dependent on Salesforce reporting. But is hard to get more detail and cohort views. Treasure Data has allowed more manipulations and allowed the Salesforce structure to change and make more sense to our sales reps, SDRs, and retention teams. This has greatly changed how we can easily report on events in the sales and how to track sales funnels much more easily. This company has already been very data-driven, so a more granular and manipulative look has greatly improved tracking and performance of our teams.,Importing data into Salesforce, which is used in flows to generate data in other fields. Managing workflows, sometimes increasing the number of runs for the end of the month tracking.,Periscope Data, Looker and Tableau Online,Tableau Online, Tableau Desktop, MarketoTreasure Data is great for budding data teams.Arm Treasure Data is used as our production data warehouse. We also use Redshift, but are increasingly moving away from that - our cleansed, production datasets primarily exist within Arm Treasure Data. Arm Treasure Data provides transparent access to data for auditors, which has been a huge business problem it's addressed. We can present specific schemas to auditors to monitor, and track all of their queries easily.,Excellent console interface. Incredibly fast processing, and simple ability to shift between Hive and Spark. Simple workflows - easy to understand and use.,Workflows could be more expansive - Python capability, for example. Data visualization would be incredibly powerful. Being able to merge directly to datasets outside of TD would be powerful.,9,Treasure Data has provided the value of a full data engineer for half the cost. Treasure Data has improved our analysts capabilities by a multiple of two. Treasure Data has provided ease of data access.,Internal processes have greatly improved as a result of implementing Arm Treasure Data. We have become more data-driven as a result of the greater data transparency that Arm Treasure Data provides. Specifically, Arm Treasure Data has been invaluable as a tool for providing simple permissions to external auditors who need access to our data.,As a tool for providing greater transparency. As a data processing engine - we perform much of our back end processing for data applications in Treasure Data. As an audit tool - TD query logs are very useful for this.,Amazon Redshift,Amazon Redshift, JIRA Software, SlackIt's OK, I like itWe use Treasure Data as the one of/main data warehouse used by the company. It's mostly used by the analytics team. Raw data is processed/aggregated here to be pushed to other downstream data sources for mainstream use/reporting. One use case is that we use it to analyze events triggered by our products to determine content correctness and trends.,JSON data parsing in SQL. Coming from MySQL, I found that being able to parse JSON data is very useful. Product support. Their support team is exceptional. Growing list of data connectors. Treasure Data has data connectors to multiple external systems like Redshift and Tableau.,Product not 100% polished. We're still encountering bugs/unexpected behavior. The SQL console, being the main medium I use to interact with the data, can use more dev/query features like saved query templates and ability to search through saved queries.,8,With data in one place, we are able to shed more light on data inconsistencies and trends allowing improvement Dashboards feeding off of Treasure Data queries are able to provide a more accurate state of the business,I wouldn't say that we're already there, but surely we're headed in that direction. More and more dashboards are being built based on data in Treasure Data to expose critical metrics to the company for better data-driven decisions.,We're planning to make use of Treasure Data to be able to import Mixpanel event data at a near real-time frequency.,Tableau Online, Amazon Redshift, MySQLData Lake for StartupsTreasure Data is being used by our R&D department essentially as a data lake. Treasure Data allowed us significantly easier access to large amounts of data, without having a team dedicated directly to its management.,Data ingestion Multiple types of query tools Flexible structure,Biggest spot of improvement would be the help system,10,One big impact Treasure Data had was it allowed us to reallocate engineering resources. The net was positive for us. Depending on the amount of data ingested monthly, the cost for Treasure Data could be high for some companies.,Treasure Data gave us the ability the access our data in near real time by engineers for situations that were very time sensitive. Additionally, given the easy to use platform, we have been able to give more junior engineers access to data, allowing them to expand our reporting capabilities.,Google BigQuery,Slack, Google ChartsGreat Start but Not at ScaleTreasureData is used to ingest analytics from our frontend and backend services, as well as to import production tables. It serves as our Data Warehouse. This allows reporting to stakeholders to be done.,Managed service: don't need to scale up the infrastructure by ourselves. Simple to use UI. Good support from TreasureData when we have problems.,Presto split hours limitation is a problem for us—we've essentially scaled quite quickly so the current plan is becoming expensive for us. It's quite slow, but that's due to lack of computational resource. When there are a large number of tables to list, the UI becomes slow and unresponsive.,6,TreasureData was quite useful in the initial stages of the data infrastructure here at Canva and has helped in answering important business questions. We're not getting too much value these days, since the next tier plan isn't economical for us.,TreasureData has helped Canva become more data-driven in some aspects, like simple reporting. Various foundational tables that are very useful in understanding our users and revenue impact has been built using TreasureData. However, it's not as helpful in running workflows that include some machine learning. Also, data ingestion is a bit harder with TreasureData than Big Query for instance.,We've integrated Embulk with TreasureData to get daily snapshots of some production tables. TreasureData has been used to run queries to validate foundational tables.,Google BigQuery, Snowflake and AWS EC2 Container Service,Apache Spark, Apache Spark MLib, TensorFlow, KerasTreasure Data ReviewArm Treasure Data is a preferred partner when it comes to implemented CDP solutions for our clients. Arm Treasure Data has a number of tools/technologies making data integration, collection, transformation, unification, enrichment, segmentation, and activation that is scalable and efficient.,Data integration and collection. Data transformation. Data activation.,CI/CD - However, there seem to be newer integrations improving this.,10,Arm Treasure Data has improved advertiser match back rates and has allowed companies to personalize their advertising messages tailored to specific segments.,Arm Treasure Data takes the pain out of integrating a variety of data sources with prebuilt connectors and frameworks. It also makes segmentation and activation much easier.,Improved data ingestion. Fast segmentation and activation. Scalable ID matching/unification.,Google BigQuery,SnowflakeSimple to use and a good solution to build a pipeline but a bit low on performanceTreasure Data is used across the whole organization. We use it to create reports to help management making business decisions. We also use its Treasure Workflow feature to schedule tasks and workflows. It allows us to run big computations during the night and create custom denormalized data sets used to feed some of our in house or third party apps.,I love Treasure data workflows. Thanks to them I can run all my computations at night and when I arrive in the morning my clean data sets are ready to be analysed. Treasure Data has good customer service. When I ask a question I always get a reply very quickly. The UI is fairly easy to use. The third party connectors to ingest data and the possibility to drop CSVs are great features.,My struggle is with the performance. There are some pages on their site that give advice on how to tune the queries. However once you apply those to good practice, it is hard to understand what happens under the hood and to make further improvements. I wish there is a more detailed documentation about this.,10,It has allowed us to free some of our lead development time since they do not have time to spend on managing our data pipeline anymore. It has allowed our data scientist to automate his work using TD workflows. It has put the measurement and interpretatiton of the data our App generates at the core of the business.,Our company is very data driven. At least 4 people in the company can right complex queries. However working with data is not their primary job so we had to hire someone who is preparing and analyzing the data full time. The goal is to create a feedback loop. Our users generate data using our app and we use that data to feed our app and improve the user experience through a more accurate search and recommendation system.,Our data scientist has written an R script that parses the digital file used to schedule TD workflows and display all the dependencies between the queries in a flow diagram. Otherwise we do things the standard way.,,Google Analytics, AdWordsArm Treasure Data ReviewWe use Treasure Data (TD) for both data warehousing and data analytics. TD is the central repository for most data due to its scalability. We make use of Treasure Data for a lot of use cases, ranging from creating ML models, BI reports to A/B test tracking.,Run big data jobs Storing large amounts of data Some User-Defined functions are extremely helpful,Tables only indexed on time No inequality JOINs,8,Positive: Storage is usually not a big concern due to the scalability Positive: Large jobs can be executed in a predictable manner Negative: Ad-hoc data is more time-consuming than other DBs,TD allows us to size business opportunities based on internal data, as well as measure the impact of initiatives based on pre-defined KPIs.,Feature store for ML Models,Amazon Redshift and Amazon S3 (Simple Storage Service),Looker, Amazon Redshift, MongoDBArm Treasure Data reviewArm Treasure Data is being used across the data side of the business for data collection, storage and queries. The warehouse structure and tables are easy to use and run queries from. This is used daily by our advertising operations team.,Data warehousing Easy querying Simple table structure,No room for improvement,10,Ease of use Efficiency,Arm Treasure Data has helped us make changes to our internal processes for data storage allowing the business to be more efficient.,Rolling out new data products More data analysis on exisiting data Upsell to clientsArm Treasure Data ReviewArm Treasure Data is being used by specific departments of our organization. Since our organization is very huge, it is not possible for all departments to use the same tools. Arm Treasure Data acts as a single stop to managing all the customer data and making sense out or raw data. It is also extremely useful for targeted marketing. It uses basic and advanced algorithms (including machine learning and AI) to understand customer patterns. It lets us understand customer needs and what to target/focus on each customer.,It has the capability to absorb big-data, which is becoming a must with tons of data on hand. Also for a bigger organization, this is a must. It is a cloud-based platform. data can be accessed from anywhere and is also secure at the same time. It has a high level of scalability with fewer overheads. There is great support available from the teams. It makes it possible to integrated data from different data sources.,Mobile support for this tool could be improved compared to other tools. Pricing can be made more flexible and customized. This will also make it cheaper for specific users or users who require only certain modules in the tool. The marketing campaigns could have a more in-depth/drill-down analysis of their reports.,9,It definitely has positive results in the ROI since we are using the tool very effectively. We have been able to focus and market to specific customers with different offers. It has helped with making more sense out of data and hence is very effective. Machine learning/AI is not fully up to the mark, but does make a difference. We have been able to save money with marketing and arranging online campaigns and newsletters to customers. Instead of mass marketing, we are able to support it logically.,Initially, we were using raw data and did not have a very clear direction on how to use it. We were working on creating an in-house tool to manage data but obviously, it would have taken too much time. We hence tried the Arm Treasure data as it was a third party tool and would save cost immediately. Also, it would help us get immediate results. We changed our team structure accordingly and assigned specific resources to just work on this tool and have our business partners use this tool to make data-driven decisions. These decisions were measured and analyzed. They proved to have better results than what we were doing, but our goal was to increase the success ration and be able to convert more customers based on their customized preferences.,Geo-based customized marketing -- we integrated with other APIs to understand customers based on their geo-location. Marketing based on ex-customers that are to be re-converted. Marketing campaigns based on reference customers -- this plays a very important role in terms of the goodwill of our company.,Amazon Redshift, Amazon Elastic MapReduce, Snowflake, Stitch, Alooma, Cloudera Enterprise, Qubole and Altiscale,Oracle Access Management, Microsoft Visual Studio Code, MS SharePointThe intelligent CDPWe are using Treasure Data as a CDP to centralize all data about final customers in one place. The data is getting imported easily then cleaned and unified. We use it to create segmentation to improve our marketing strategy and save media waste. It also empowers us with some predictive segment for churn and potentially new customers.,Many connectors. Handle huge amount of data. Easy of use.,No Krux integration yet. Not easy to measure the return of campaigns.,8,Reduce media waste. Do intelligent predictions.,Instead of doing massive broadcast advertisement we learned how to customize our advertisement and message to the good people at the right time and on the right device with the right message.,Targeted audiences. Find hidden audiences.,SAP HybrisA great all-in-one tool for data management and unsiloe-ingTreasure Data (TD) was used as a Customer Data platform in order to improve the quality of marketing having a single view of the customers. It was used across all the world units but mostly by marketing areas. It was used in order to unify the data about the customers that are stored across several (too many) databases.,The first and most important feature is that it is completely out of the box. You contract Arm Treasure Data and the day after you are able to ingest data, manage it, segment the audiences and then export it. The power of calculation. Even having billions of records across hundreds of databases, we never wonder about the power of Arm Treasure Data to ingest and manage it. The customization of scripts. It is really easy and intuitive to write script inside the platform and even workflows (series of customizable on the fly queries). The chat support, available 24/7, is a really nice option for a global company!,Some features, important for our business use cases, were in development such as writing scripts (other than presto/hive). There was no SFTP for data ingestion provided out of the box, this could be nice-to-have.,8,In marketing, the ROI is hard to measure and we are working on this for next year. For sure we made 2 types of earnings: Savings: sending fewer messages that were duplicates (many emails per person, brand cannibalism, etc.) Quality Improvement: the messages we send are better targeted by better knowing the consumer. I don't see negative impacts from this platform.,Indeed, this platform helps a lot to be more data-driven in the company. TD did not replace something we had in place, it is a piece that we had between some systems. The implementation was done by a consulting company which allowed us not to hire dedicated people. Now that it is live, there is just a little need for support. The changes in processes are slight. There are some changes for website tagging, which is just a one-time thing per website. Some training was given to marketers to understand the power of the tool, which is on the way.,Having Hivemall integrated with the platform allows us to go further in intelligent manipulation of data.,,Slack, Trello, Workplace by Facebook, AnacondaTreasure Data will let you fully, and EASILY, understand your data.Treasure Data is being used across the entire organization. We are using it to define churn probability of subscribers, behavioral analysis of our online readers, event attendees that have attended multiple events, digital advertising reports, multiple integrations with our CRM and email automation systems. We have connected it to Tableau to give us a strong data visualization element of our raw data. The biggest business problem that Treasure Data addresses is that it gives us a single platform for data collection and analysis.,Treasure Data is very flexible for ingesting different data sets. The native integrations that they have built are among the majority of the systems that we have, therefore creating a data lake was relatively simple. The product team at Treasure Data was able to build a new connector, as a partner to us as a client, for managing our event attendees and revenue impact.,One of the issues that we faced, when onboarding, was the lack of understanding around what we were trying to accomplish as a company, and not being made aware of some of the functionality in Treasure Data. The documentation doesn't always have all of the steps, from a layman's perspective, to be able to set up more intricate custom connections. We had an issue, specific to our needs, where the Doubleclick For Publishers (DFP) API connection wouldn't use a dynamic date range for data ingestion, therefore we have to change the date query each month, on the last day of the month, to pull in the latest digital advertiser information.,10,Treasure Data has provided an immediate positive impact on seeing the details of the business, without having to aggregate multiple spreadsheets and use pivot tables. Treasure Data has helped to provide a positive predictive model for potential customers to upgrade their spending with the company, providing an immediate list of prospective leads to provide to the sales team. Treasure Data has now allowed us to define our LTV and 360-degree view of our customers, where we struggled with this before.,We are still working towards being data-driven. Treasure Data has been a significant factor in that transition, for us. We are now able to share reports, do real-time queries and analysis, and showcase the data into a more manageable standpoint, using visualization to executive leadership and general staff. This has led to more questions about other areas of data that we haven't had in the past and aligns the corporate interests in growth using data.,Currently, we were pulling analytics reports from DFP and creating a new client report, each month, for a digital advertising client, having a very manual process. We didn't know that Treasure Data had a Reporting tool until after we were onboard. We were able to leverage that tool and use an integration to pull in the analytics information, at near real-time, to have dynamic Dashboards for our clients. Being able to cross-query multiple data sets was an expectation from the beginning, but what we found, prior to Treasure Data, is that most systems made this a complicated process. Treasure Data made it much simpler. Being able to use predictive scoring was an unexpected benefit for us, helping to leverage the insights regarding subscribers to our products.,Looker and Stitch,Google Analytics, Parse.ly, Tableau OnlineMake sure you give Treasure Data a tryAt Exostatic, we help companies run their data pipelines and successfully implemented Treasure Data in some of them. Treasure Data is a solid partner with a truly effective ETL platform.,Flexibility Power Ability to connect to multiple data sources,Nothing I think of at the moment, Treasure Data is always responsive when an improvement is needed,10,Treasure Data is a powerful data platform and definitely increases our effectiveness.,It is our mission to encourage our clients to become more data-driven, to show them how data analysis can help them reach new heights with their business. Treasure Data is our partner of choice in implementing a powerful data platform to suit our clients' needs.,Use it as an intermediary to pre-process data before piping it in Salesforce, Marketo, Hubspot,...,Upsight, Swrve and Domo,App Annie, Chartboost, Fyber, Apptopia, Tableau Server, Tableau Desktop, Tableau Online,8,7A Great Way to Kickstart Data Engineering and AnalyticsWe use Treasure Data to collect and transform data from multiple sources for the purpose of product analytics.,Great library of connectors Workflow engine is simple, but in a good way Presto query performance is very good Support is very good, especially with live chat,Presto support is missing key types making it surprisingly verbose to do this as you need to cast things back and forth Lack of support for deploying our own connectors Cannot write Ruby or Python code in workflows,9,We were able to create a true product analytics capability in record time We we able to democratise product analytics by exposing it in our BI tools and in Salesforce thanks to Treasure Data,Yes, we have definitely become more data driven since adopting Treasure Data. The main benefit is first having the data, and then being able to distribute it to where it is needed to make data-driven decisions. For us, that is in Salesforce for customer success and account management, Tableau for exec reporting, and Amplitude for our product managers and designers.,Send product metrics to Salesforce Centralised digital analytics using Treasure Data Javascript SDK, then syndicate to other tools like Amplitude As a data warehouse using Presto,Alooma, Astronomer, Segment, Sisense and Keboola Connection,Tableau Desktop, Tableau Server, LookerGood product but can improve some functionalityIt is used by BI department to fill the gap between transactional database and data warehouse.,API connection for multi sources are made very user friendly Workflow option makes it easy to manage day to day manual activities Easy to join multiple datasources in one code,User access can be more layered Some of the programming language functionality are not available which makes it hard for developers to find work arounds.,8,None None None,Linking our internal database and TD Api data sources are very helpful to achieve better results in understanding of company's over all progress in certain area.,none,Google BigQuery and Azure SQL Database,Amazon Relational Database Service, MySQL, Azure SQL DatabaseLet's my team focus on the value we can bring, not building data pipelinesTreasure Data is used by the Data and Analytics team to act as the basis for our entire data infrastructure. Treasure Data makes the process of ingesting, organising, processing and then outputting data extremely easy, centralised and reliable. It allows our small data team to focus on the outcomes that the data supports, the use-cases, instead of dev-ops. As such, the data inside of TD is used by everyone in the organisation in some form or another, from making data available to Looker, our BI tool, to pushing audiences out to Advertising Platforms, to generating complicated reporting for specific management stakeholders. The easy of not having to build connectors into services, or a workflow management system is a major benefit to us.,Workflow Management -> Easy to integrate saved queries, centralised, good debugging, powerful Directed Acyclic Graph functionality Support -> Absolutely outstanding support, I have never had an issue which has been put in the "too hard, cannot fix, work around" pile. Effective Management of Hadoop Clusters -> Interactive querying of our Hadoop clusters, never having to think about the dev-ops, availability or CPU load of our queries is an incredible force multiplier for us,The breadth of connectors to APIs is good, but some of the connectors are at best confusing, and at worst outright hostile to users. Some of the errors and connection settings are incomprehensible. I would like to be able to run simple arbitrary scripts in the workflows, though I understand why this is hard. I would like a breakdown of utilisation by query, to allow me to understand which elements of my workflows are potentially so inefficient as to be causing problems. While TD's compute power is (to me) effectively infinite this isn't a blocking problem. However on the understanding that it actually is finite, this is important. This will get more important the more we set up.,10,It enables us to do things that no one else our size can do, and which cause bigger vendors like Google with BigQuery to get very uncomfortable when I tell them we can do everything they consider core USPs. The most direct impact on ROI is supporting the creation and syndication of audiences to ad platforms based upon behavioural data which can only be stitched together between several sources (Shopify and Zendesk and Segment).,Treasure Data allows our marketing to both answer more complicated questions about our customers and to reliably and consistently push data to our tools for stakeholders to do their own reporting. As such, the ad-hoc request workload for the Data and Analytics team has significantly lightened, and the appetite for hypothesis driven marketing campaigns and testing has increased in the Marketing Team.,The JS API allows us to easily connect Node and Python scripts, which perform scraping and data analysis tasks, directly to our storage. This was surprisingly easy and painless Easy access to GA reporting connectors allows you to hack together more complicated reports by querying the endpoint frequently and retaining data, than a single report would allow.,Snowflake and Amazon Redshift,Looker, Segment, Amazon Redshift, KlaviyoTreasureData might be the right choice for the right environment.TreasureData is being used across about half of the organization. It gives us the ability to ingest, store and analyze a very large volume of gaming events. It also helps us to get near instantaneous data events from our games. Ability to handle large volume of events is why we went with TreasureData in the first place.,TreasureData is excellent in integration with various software and services. Implementation of the their SDK is also very easy. TreasureData SDK works well in our applications and does not crush.,Data management is very challenging with TreasureData (can't delete records, update tables, create indexes, etc). Analyzing and queries tables with very large number of records is near impossible or takes a very long time. To effectively visualize data we need to first export it to SQL and the run our viz tools due to the reason above.,8,TreasureData allowed us to start measuring metrics in our apps which we never been able to before. I would say that at this point TreasureData is most likely ROI positive, although we haven't done extensive analysis.,We definitely have access to detailed data we did not have before with TreasureData. This allows us to make data-driven business decisions on how to operate our mobile applications better. Our monetization strategies in our applications have improved as a result of us examining the detailed application events by a good margin.,We schedule a lot of our data aggregation in TreasureData and push the data to MS SQL for faster analysis and visualizations. We are looking into utilizing TreasureData's API to do two-way communication and data passing.,Leanplum and App Annie,Tableau Desktop, Tableau Server, Snowflake,5,1,Ad Hoc Queries Aggregation of Daily KPIs Integration with various other tools,Two-way communication with TreasureData's API,8,Yes,Price Product Features Product Usability,No, I think TreasureData is what we need.,Implemented in-house,No,Change management was a small part of the implementation and was well-handled,Naming conventions in the mobile SDK were not followed, so column names in the tables can be different across games.,8,Self-taught,Documentation is excellent, so learning without training is not a problem.,No,9,No,My queries ran out of memory, support helped me optimize my Presto SQL to run my queries.,Running AdHoc Presto queries on relatively small data sets. Scheduling queries and workflows are very easy.,Running Hive queries on very large data sets.,8Disruption in Data Services - Unveiling the true potential of Treasure DataWe use Treasure Data within our mobile games to track in-app events. The entire company uses the data however the major use is within monetization. Treasure Data’s platform is very much misunderstood. TD is not just a cloud storage or hosted middleware solution, it is an entire information management platform which offers cradle to grave data services from ETL to Stats. TD SDK + Digdag + TD workflow + TD storage + TD Connections + TD machine learning = IT/BI/DA off the shelf,It is reliable- uptime is 99.99% Job processing is easy The new workflow tool is outstanding. It allows various data processing options with extensive metadata surrounding the success of the workflow. 100% dynamic including options for parallel processing jobs. One of the best features in my option. And with digdag Easy integration,Td needs to focus on increased processing speed. Not by adding more resources but rather indexing partitioning or allowing primary keys outside of time WhatTreasure Data offers requires a change of mindset with a focus on the big picture. I believe it is largely misunderstood. More education and really- you need a solution architect to ask how the technology is used and not why Data mapping from their sdk to Treasure Data should be more flexible,10,Positive impacts have been within monetization as we are now able to manage ad partners and marketing more efficiently. Td saved money due to not buying hardware and storage internally. Storing 100tb+ is very expensive elsewhere Stand up time for TD was 1000% less than other options,As mentioned, without td we could not use or see user events. We are now more data driven as well as more profitable due to this integration.,Digdag workflow as etl management,Snowflake, AWS Elastic Beanstalk, Amazon S3 (Simple Storage Service), Treasure Data and Activ8 Intelligence,SQL Server Integration Services, Microsoft SQL Server, Tableau Server,100,2TD RevewTreasure data is used by a select analysts and data engineers as the main ETL platform for event based data. Our company includes two main sets of data, app analytics events logged when users interact with our apps and static data that is more business/inventory/finance focused. Treasure data deals with the former (in correlation with the rest of the datasets that we house at our company) to aggregate and transform raw data into actionable usable tables,Connecting with other platforms. Love the connectors that TD offers and how easy they are to use Scheduled queries are also very easy to manage and incorporate in workflos TD UDFs are particularly handy and a great way to simplify code,Searching for past older jobs can be tedious sometimes. wish there was a more robust ability to search oder queries,9,Tremendous positive impact to take all disparate data sources and bring them together for cohesive data structures Ability to ingest via workflows and implement controls and filters before production data is tremendous,Treasure Data has allowed us to dig deep into our app events data and understand how users are utilizing our apps. It has also allowed us to validate or myth bust a lot of speculations that were made about our products before having the ability to look under the hood and see if the data is actually approving a lot of claims that were made in the past. TD has absolutely moved us into being a more data centric company,Validating revenue recognition through complex queries and data analysis/cleanup,,Amazon RedshiftTreasure Data gave us superpowers.We use Treasure data to collect and store information from all departments within the business, including web analytics, marketing spend, email activity, and customer engagement. The data is also used to build reports from board level reporting to day to day actionable reports for marketing, customer services, and product development. It helps us solve a range of data-driven problems across our whole business.,Easily stores a large amount of data - meaning you're not put off collecting things that may be useful in the future. We don't have to be conservative with what we store. Connects to multiple data sources - so data generated outside platforms we control - like Facebook, Google Adwords - we can pull key data from these places too. Quick querying - the query writing in Treasure data is helpful, they are also good UDFs that speed up and simplify queries.,We want to see our data, so to visualise it we need to use another tool on top, or export it. At the moment, you can't search saved queries by the tables they use - I think it would be useful.,10,Treasure data has helped make it easy to give data to more people so people can improve at their roles. Treasure data enables us to do analysis and build useful tools with our data, some of which have saved us money by negating the need for additional tools. Using Treasure data has helped us spot and act on opportunities to save and make more money.,Since we started using treasure data, our product team has become far more versed in data and eager to track and report on changes they make to the product. People are more likely to ask complex questions or request detailed data sets because they know that most requests can be fulfilled and in reasonable time.,We've built tools we might not have expected, like an Adwords bidding tool.,Heroku, Trello, Zapier, MaxemailReliable data warehouse as a serviceIt is used as a data warehouse. Raw data containing operative business information is continuously ingested to Treasure Data. Different batch jobs are continuously running to aggregate data based on a different number of dimension to achieve relevant granularities for specific use cases. The data is used across the whole organisation for: reporting to customers, troubleshooting by tech support, analysis and feature design by R&D, etc.,Very reliable data ingestion to their warehouse Fast querying capabilities using Presto and Hive Good API for programatic access to the data,Adding support for not only batch processing but also streaming data Better grouping and organization of saved queries and jobs,9,It was positive to not need to implement a data warehousing solution ourselves It allowed us to efficiently store important business (e.g.billing) information in real time,We definitely use Treasure Data to become more data driven. Even though we do not have a dedicated data scientist who would continuously crunch the data from Treasure and come up with proposals on how our solution and processes can be improved, we are frequently using Treasure to validate R&D ideas and potential product features prior to implementation using only historic data.,For implementing revenue boasting algorithms based on historic data For implementing cost saving algorithms using historic data,Docker, Aerospike Database, MemSQLTreasure Data - definitely some hidden gems hereShortening the time to market for getting data in the hands of users and easily integrating it into other platforms to centralize this data in a single place was a huge win for us. The ability to then query across data sets from different source systems at a large scale was great. The performance on very large data sets (billions of rows) was pretty good as well.,Very easy to get up to speed on the platform, the web interface was simple and easy to use and we were quickly able to leverage our teams existing SQL based skill set without having to know a ton about the underlying HDFS based platform Treasure Data sits on top of. Speed of development was great and built-in connectors for various cloud data sources and destinations were excellent. The ability to write directly to data sets for Tableau Online was a nice feature.,The workflow scheduling piece, while very robust was still too code/script heavy for what other integration platforms do easily in a simple UI. The UI will need to improve here to accommodate all the underlying features and functionality that can be implemented via the scripting language. Updating data does not exist as part of the platform features so you just have to know what you want to use the platform for before implementation. This would be a nice feature enhancement.,9,Our clients are seeing immediate returns on their investment because the platform allows them to quickly do what has traditionally taken much longer to get done from an integration platform perspective.,This is not applicable to us as we are an implementer of the platform for our clients, not a direct user of the platform.,None at the moment as we are not directly using the product, rather have implemented it for our customers.,None,10,NoTreasure Data - it's pretty goodWe have a huge amount of data that requires processing, and treasure data provides the big data solutions required to handle it all. We have hundreds of terabytes of data that needs aggregation and filtering before it is in a state that can be meaningfully used by our analysts to make business decisions.,Handles queries on big data well Easy to use in conjunction with other data warehousing and data processing tools.,Web application often not responsive when the database grows to too large a size.,8,Its facilitated our ability to leverage huge amounts of data to make better business decisions.,Yes since our company bases its decisions on data more than anything else, having Treasure Data has one of our main data services, and an integral part of most of our data pipelines means it has been critical to all internal data processes.,Looker, MongoDB, Amazon Redshift
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Arm Treasure Data
94 Ratings
Score 8.3 out of 101
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Arm Treasure Data Reviews

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Arm Treasure Data
94 Ratings
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Jaime DyBuncio profile photo
Score 8 out of 10
Vetted Review
Verified User
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We use Arm Treasure Data as our ETL hub. We extract data using its connectors to several sources, such as Salesforce. We transform data using Treasure's query tools and also use it to build scheduled workflows. And we ultimately load ready to use tables into visualization tools such as Tableau.

This process allows us to combine and centralize our data into a format to best make use of it to uncover business insights and create reporting for accountability and tracking purposes.
  • Building Workflows is easy using Treasure's interface. You can run many jobs in parallel or in sequence and those jobs can run at scheduled times and create the right tables and data loads you need.
  • Being able to write queries (in Presto or Hive) using the all the data sources you have brought in to either create tables, run a query, or export data to a variety of sources is seamless and intuitive.
  • Extracting data from a variety of sources is fairly easy.
  • Very responsive and helpful customer service who you can reach easily by Chat.
  • Pricing is a bit of a black box. We are currently priced on split hour usage and some spikes come out of nowhere and leave us seeking answers (and sometimes finding unsatisfactory ones).
  • Some jobs will fail, causing workflows to be interrupted due to a product change or a one-time product related issue. We usually contact Support in these cases, and while they are incredibly responsive and helpful, it would be great to have more proactive communication.
  • Treasure's UI leaves us wanting more in terms of organization and controls, especially as we scale and grow the number of data sources, queries, and workflows.
Treasure Data is a great use case for a company who is seeking to use a third-party (and at times, expensive) solution to automate the centralization of their data, even if it comes from a broad array of sources, and who has the resources to then create unified data sources and load them into a variety of options, be it Google Sheets, Tableau, or to even load enriched data into their own CRM to make the best use of it.
Read Jaime DyBuncio's full review
Eunice Lau profile photo
Score 8 out of 10
Vetted Review
Verified User
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We utilize Treasure Data as a way to bring in data from SFDC and translate it in a useful way for Tableau. It is a workflow management tool, SQL tool, and exporter. SFDC reporting has limitations especially for cohort analysis, so we need to manipulate the data outside of SFDC. TD provides a great way to import and export data we need into SFDC. The entire company utilizes the data from SFDC. Only select analysts are able to have access to Treasure Data itself. These analysts do not have experience in managing data and data sources, so Treasure Data has been a helpful tool that assists with the gap.
  • Importing data from Salesforce and other sources - with no or little background in data sources, Treasure Data has been useful with assisting the gap.
  • Exporting data into Salesforce and Tableau is very simple to set up and can be easily scheduled.
  • Support from Treasure Data is a live chat and has been VERY helpful with assisting a lot of the little issues that we run into.
  • There are often bugs when they update the source connections. However, they are diligent and have been correcting the issues in a timely matter.
  • There are often slow downs with our workflows and increase in Presto usage hours that aren't explainable. We don't change the queries, but we see slow downs over time.
Treasure Data is great for companies that do not have a data engineer that helps with constant maintenance and updates to the data tables (sources like Salesforce). This tool is very user-friendly and helps with the management of data. However, it cannot handle large amounts of data. There isn't enough memory [unless the company is willing to pay more] to handle complicated and large queries.
Read Eunice Lau's full review
Darrin Lim profile photo
Score 9 out of 10
Vetted Review
Verified User
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Arm Treasure Data is used as our production data warehouse. We also use Redshift, but are increasingly moving away from that - our cleansed, production datasets primarily exist within Arm Treasure Data.
Arm Treasure Data provides transparent access to data for auditors, which has been a huge business problem it's addressed. We can present specific schemas to auditors to monitor, and track all of their queries easily.
  • Excellent console interface.
  • Incredibly fast processing, and simple ability to shift between Hive and Spark.
  • Simple workflows - easy to understand and use.
  • Workflows could be more expansive - Python capability, for example.
  • Data visualization would be incredibly powerful.
  • Being able to merge directly to datasets outside of TD would be powerful.
Arm Treasure Data is well suited to providing multiple users with a console interface that abstracts away messy connection details. Not having to worry about how to connect to Treasure Data has been a lifesaver - it's a major point that separates it from Redshift, especially for less technical users. Furthermore, it removes the need to install any excess software. It's a great way to have a data warehouse stood up quickly that's easy to access.
Read Darrin Lim's full review
Rolando Bernabe Tribo profile photo
July 11, 2019

It's OK, I like it

Score 8 out of 10
Vetted Review
Verified User
Review Source
We use Treasure Data as the one of/main data warehouse used by the company. It's mostly used by the analytics team. Raw data is processed/aggregated here to be pushed to other downstream data sources for mainstream use/reporting. One use case is that we use it to analyze events triggered by our products to determine content correctness and trends.
  • JSON data parsing in SQL. Coming from MySQL, I found that being able to parse JSON data is very useful.
  • Product support. Their support team is exceptional.
  • Growing list of data connectors. Treasure Data has data connectors to multiple external systems like Redshift and Tableau.
  • Product not 100% polished. We're still encountering bugs/unexpected behavior.
  • The SQL console, being the main medium I use to interact with the data, can use more dev/query features like saved query templates and ability to search through saved queries.
Treasure Data is good at data ingestion, having built-in data connectors to a growing list of external systems. It also has decent scheduling and workflow capabilities but if your job workflow is complex, it might not be the ideal tool.
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Mike Pedersen profile photo
Score 10 out of 10
Vetted Review
Verified User
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Treasure Data is being used by our R&D department essentially as a data lake. Treasure Data allowed us significantly easier access to large amounts of data, without having a team dedicated directly to its management.
  • Data ingestion
  • Multiple types of query tools
  • Flexible structure
  • Biggest spot of improvement would be the help system
From our experience, Treasure Data is perfect for capturing large amounts of data and allowing smaller teams the ability to access that data like any other database. Larger organizations might have the ability to recreate in-house.
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Score 6 out of 10
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TreasureData is used to ingest analytics from our frontend and backend services, as well as to import production tables. It serves as our Data Warehouse. This allows reporting to stakeholders to be done.
  • Managed service: don't need to scale up the infrastructure by ourselves.
  • Simple to use UI.
  • Good support from TreasureData when we have problems.
  • Presto split hours limitation is a problem for us—we've essentially scaled quite quickly so the current plan is becoming expensive for us.
  • It's quite slow, but that's due to lack of computational resource.
  • When there are a large number of tables to list, the UI becomes slow and unresponsive.
It's quite well suited when you're a smaller company, not so when you have heaps of events coming in like Canva. It's also useful when there is a lack of resources to manage your own infrastructure. The easy to use UI, in general, makes it easy for analysts, and sometimes, stakeholders to write SQL queries and reports.
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September 11, 2019

Treasure Data Review

Score 10 out of 10
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Verified User
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Arm Treasure Data is a preferred partner when it comes to implemented CDP solutions for our clients. Arm Treasure Data has a number of tools/technologies making data integration, collection, transformation, unification, enrichment, segmentation, and activation that is scalable and efficient.
  • Data integration and collection.
  • Data transformation.
  • Data activation.
  • CI/CD - However, there seem to be newer integrations improving this.
Treasure Data is well-suited to unify disparate/decoupled data sources into master views allowing for quick activation. It is the ultimate CDP.
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Score 10 out of 10
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Verified User
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Treasure Data is used across the whole organization. We use it to create reports to help management making business decisions. We also use its Treasure Workflow feature to schedule tasks and workflows. It allows us to run big computations during the night and create custom denormalized data sets used to feed some of our in house or third party apps.
  • I love Treasure data workflows. Thanks to them I can run all my computations at night and when I arrive in the morning my clean data sets are ready to be analysed.
  • Treasure Data has good customer service. When I ask a question I always get a reply very quickly.
  • The UI is fairly easy to use.
  • The third party connectors to ingest data and the possibility to drop CSVs are great features.
  • My struggle is with the performance. There are some pages on their site that give advice on how to tune the queries.
  • However once you apply those to good practice, it is hard to understand what happens under the hood and to make further improvements.
  • I wish there is a more detailed documentation about this.
If you want to use one platform to manage your whole data pipeline from collecting the data on your app, to importing third party data using using external APIs, to running your queries and scheduling workflows Treasure Data is very good.

If you already have some mature tooling that performs one or several of those tasks it may be less appropriate.
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Score 8 out of 10
Vetted Review
Verified User
Review Source
We use Treasure Data (TD) for both data warehousing and data analytics. TD is the central repository for most data due to its scalability. We make use of Treasure Data for a lot of use cases, ranging from creating ML models, BI reports to A/B test tracking.
  • Run big data jobs
  • Storing large amounts of data
  • Some User-Defined functions are extremely helpful
  • Tables only indexed on time
  • No inequality JOINs
TD is well suited for operating on large sets of data. The User-Defined Functions (UDFs) help with log-type tables.

On the other hand, TD does not do well with tables that require row updates. TD is also not ideal for looking at very long time ranges, since you cannot optimize queries other than on the time index.
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Sarah Kavanagh profile photo
January 28, 2019

Arm Treasure Data review

Score 10 out of 10
Vetted Review
Verified User
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Arm Treasure Data is being used across the data side of the business for data collection, storage and queries. The warehouse structure and tables are easy to use and run queries from. This is used daily by our advertising operations team.
  • Data warehousing
  • Easy querying
  • Simple table structure
  • No room for improvement
Arm Treasure Data is a great data warehousing option for small/medium businesses requireing data collection, storage and/or third-party connections.
Read Sarah Kavanagh's full review
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February 09, 2019

Arm Treasure Data Review

Score 9 out of 10
Vetted Review
Verified User
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Arm Treasure Data is being used by specific departments of our organization. Since our organization is very huge, it is not possible for all departments to use the same tools. Arm Treasure Data acts as a single stop to managing all the customer data and making sense out or raw data. It is also extremely useful for targeted marketing. It uses basic and advanced algorithms (including machine learning and AI) to understand customer patterns. It lets us understand customer needs and what to target/focus on each customer.
  • It has the capability to absorb big-data, which is becoming a must with tons of data on hand. Also for a bigger organization, this is a must.
  • It is a cloud-based platform. data can be accessed from anywhere and is also secure at the same time.
  • It has a high level of scalability with fewer overheads. There is great support available from the teams.
  • It makes it possible to integrated data from different data sources.
  • Mobile support for this tool could be improved compared to other tools.
  • Pricing can be made more flexible and customized. This will also make it cheaper for specific users or users who require only certain modules in the tool.
  • The marketing campaigns could have a more in-depth/drill-down analysis of their reports.
Overall the software is excellent and can be used for various purposes and customer data management. It is very well suited when there is big-data involved. I think the leads could be managed slightly better, and the software can have more integration points with other software. Improving mobile support and being able to fetch data real-time will be of great help. This helps in managing an online and non-online campaign at the same time.
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December 27, 2018

The intelligent CDP

Score 8 out of 10
Vetted Review
Reseller
Review Source
We are using Treasure Data as a CDP to centralize all data about final customers in one place. The data is getting imported easily then cleaned and unified. We use it to create segmentation to improve our marketing strategy and save media waste. It also empowers us with some predictive segment for churn and potentially new customers.
  • Many connectors.
  • Handle huge amount of data.
  • Easy of use.
  • No Krux integration yet.
  • Not easy to measure the return of campaigns.
Arm Treasure Data can be used if your customer data divided into several silos, from several sources.
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Score 8 out of 10
Vetted Review
Verified User
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Treasure Data (TD) was used as a Customer Data platform in order to improve the quality of marketing having a single view of the customers. It was used across all the world units but mostly by marketing areas. It was used in order to unify the data about the customers that are stored across several (too many) databases.
  • The first and most important feature is that it is completely out of the box. You contract Arm Treasure Data and the day after you are able to ingest data, manage it, segment the audiences and then export it.
  • The power of calculation. Even having billions of records across hundreds of databases, we never wonder about the power of Arm Treasure Data to ingest and manage it.
  • The customization of scripts. It is really easy and intuitive to write script inside the platform and even workflows (series of customizable on the fly queries).
  • The chat support, available 24/7, is a really nice option for a global company!
  • Some features, important for our business use cases, were in development such as writing scripts (other than presto/hive).
  • There was no SFTP for data ingestion provided out of the box, this could be nice-to-have.
Arm Treasure Data is really well designed for data management. It is a high-quality data lake, but even more than that there are many features developed specifically for real-life issues that most data engineers are used to encountering and can be hard to solve. For instance, the management of the jobs is really easy to handle and understand at first sight. Also, the parametrization in workflows made the deployment of the tool in all zones of the world as easy as a copy/paste. It would have taken weeks to adapt the workflow to the specificity of each country otherwise (zip code, phone numbers, SSN equivalent, etc.)
On the other hand, the creation of not-available connectors (not that many, but existing) inside the platform may be improved. It is now configurable only in CLI.
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Mark Chiles profile photo
Score 10 out of 10
Vetted Review
Verified User
Review Source
Treasure Data is being used across the entire organization. We are using it to define churn probability of subscribers, behavioral analysis of our online readers, event attendees that have attended multiple events, digital advertising reports, multiple integrations with our CRM and email automation systems. We have connected it to Tableau to give us a strong data visualization element of our raw data. The biggest business problem that Treasure Data addresses is that it gives us a single platform for data collection and analysis.
  • Treasure Data is very flexible for ingesting different data sets.
  • The native integrations that they have built are among the majority of the systems that we have, therefore creating a data lake was relatively simple.
  • The product team at Treasure Data was able to build a new connector, as a partner to us as a client, for managing our event attendees and revenue impact.
  • One of the issues that we faced, when onboarding, was the lack of understanding around what we were trying to accomplish as a company, and not being made aware of some of the functionality in Treasure Data.
  • The documentation doesn't always have all of the steps, from a layman's perspective, to be able to set up more intricate custom connections.
  • We had an issue, specific to our needs, where the Doubleclick For Publishers (DFP) API connection wouldn't use a dynamic date range for data ingestion, therefore we have to change the date query each month, on the last day of the month, to pull in the latest digital advertiser information.
Treasure Data is well suited for pulling in multiple data sets, to help define and understand your audience, business, predictive scoring and having a central platform for doing data analysis and data science.

What it's not well suited for, however, is heavy charting and data visualization. We've had limitations using Treasure Reporting.
Read Mark Chiles's full review
Nicolas Nadeau profile photo
Score 10 out of 10
Vetted Review
Verified User
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At Exostatic, we help companies run their data pipelines and successfully implemented Treasure Data in some of them. Treasure Data is a solid partner with a truly effective ETL platform.
  • Flexibility
  • Power
  • Ability to connect to multiple data sources
  • Nothing I think of at the moment, Treasure Data is always responsive when an improvement is needed
Treasure Data is particularly useful when companies have numerous data sources to connect in order to be able to make strategic decisions.
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Scott Arbeitman profile photo
Score 9 out of 10
Vetted Review
Verified User
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We use Treasure Data to collect and transform data from multiple sources for the purpose of product analytics.
  • Great library of connectors
  • Workflow engine is simple, but in a good way
  • Presto query performance is very good
  • Support is very good, especially with live chat
  • Presto support is missing key types making it surprisingly verbose to do this as you need to cast things back and forth
  • Lack of support for deploying our own connectors
  • Cannot write Ruby or Python code in workflows
If you are a mid-size company with disparate data sources and you want to build a data lake and/or data warehouse, Treasure Data may be a good fit. If you want to syndicate data to other data sources, when supported by Treasure Data, beyond a data warehouse, such as to Salesforce or Amplitude, Treasure Data is also a great fit.

For most of your data collection and analytical needs, Treasure Data is a great stack.

If you have very complex privacy requirements, esoteric data stores or have a capable and unconstrained infrastructure team, a better path may be to build instead of buy in this space.
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Zankhana Shah profile photo
Score 8 out of 10
Vetted Review
Verified User
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It is used by BI department to fill the gap between transactional database and data warehouse.
  • API connection for multi sources are made very user friendly
  • Workflow option makes it easy to manage day to day manual activities
  • Easy to join multiple datasources in one code
  • User access can be more layered
  • Some of the programming language functionality are not available which makes it hard for developers to find work arounds.
Bringing Google Analytics data via API into the environment was very helpful as we were able to utilized GA attributes with our internal KPIs.
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Score 10 out of 10
Vetted Review
Verified User
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Treasure Data is used by the Data and Analytics team to act as the basis for our entire data infrastructure.

Treasure Data makes the process of ingesting, organising, processing and then outputting data extremely easy, centralised and reliable. It allows our small data team to focus on the outcomes that the data supports, the use-cases, instead of dev-ops.

As such, the data inside of TD is used by everyone in the organisation in some form or another, from making data available to Looker, our BI tool, to pushing audiences out to Advertising Platforms, to generating complicated reporting for specific management stakeholders. The easy of not having to build connectors into services, or a workflow management system is a major benefit to us.
  • Workflow Management -> Easy to integrate saved queries, centralised, good debugging, powerful Directed Acyclic Graph functionality
  • Support -> Absolutely outstanding support, I have never had an issue which has been put in the "too hard, cannot fix, work around" pile.
  • Effective Management of Hadoop Clusters -> Interactive querying of our Hadoop clusters, never having to think about the dev-ops, availability or CPU load of our queries is an incredible force multiplier for us
  • The breadth of connectors to APIs is good, but some of the connectors are at best confusing, and at worst outright hostile to users. Some of the errors and connection settings are incomprehensible.
  • I would like to be able to run simple arbitrary scripts in the workflows, though I understand why this is hard.
  • I would like a breakdown of utilisation by query, to allow me to understand which elements of my workflows are potentially so inefficient as to be causing problems. While TD's compute power is (to me) effectively infinite this isn't a blocking problem. However on the understanding that it actually is finite, this is important. This will get more important the more we set up.
The only scenario where I would not suggest Treasure Data, is either in organisations which are too small to pay the fee and must resort to open source solutions, or organisations so large and sophisticated that limitations around workflows and connectors are more critical than the overwhelming efficiency saving.

TD is good for any team which does not wish to invest significant resources in developing and maintaining their data infrastructure. Even teams with dedicated Data Engineers should benefit from those engineers working on more interesting issues than "keeping the lights on".
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Score 8 out of 10
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Verified User
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TreasureData is being used across about half of the organization. It gives us the ability to ingest, store and analyze a very large volume of gaming events. It also helps us to get near instantaneous data events from our games. Ability to handle large volume of events is why we went with TreasureData in the first place.
  • TreasureData is excellent in integration with various software and services.
  • Implementation of the their SDK is also very easy.
  • TreasureData SDK works well in our applications and does not crush.
  • Data management is very challenging with TreasureData (can't delete records, update tables, create indexes, etc).
  • Analyzing and queries tables with very large number of records is near impossible or takes a very long time.
  • To effectively visualize data we need to first export it to SQL and the run our viz tools due to the reason above.
TreasureData is well suited for small to medium companies who don't have a very large data sets, and need to be able to integrate with a variety of various software or services. For very big companies with large amounts of data and a decent Data Engineering team, Treasure data might not the right fit.
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Cody Jannetti profile photo
Score 10 out of 10
Vetted Review
Verified User
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We use Treasure Data within our mobile games to track in-app events. The entire company uses the data however the major use is within monetization. Treasure Data’s platform is very much misunderstood. TD is not just a cloud storage or hosted middleware solution, it is an entire information management platform which offers cradle to grave data services from ETL to Stats. TD SDK + Digdag + TD workflow + TD storage + TD Connections + TD machine learning = IT/BI/DA off the shelf
  • It is reliable- uptime is 99.99%
  • Job processing is easy
  • The new workflow tool is outstanding. It allows various data processing options with extensive metadata surrounding the success of the workflow. 100% dynamic including options for parallel processing jobs. One of the best features in my option. And with digdag
  • Easy integration
  • Td needs to focus on increased processing speed. Not by adding more resources but rather indexing partitioning or allowing primary keys outside of time
  • WhatTreasure Data offers requires a change of mindset with a focus on the big picture. I believe it is largely misunderstood. More education and really- you need a solution architect to ask how the technology is used and not why
  • Data mapping from their sdk to Treasure Data should be more flexible
Treasure Data is meant to be used for large data. If your collecting over 100gb of data daily Treasure Data is your plan form to support. The best scenario is to connect Treasure Data directly to the source of data. Relaying data from source to internal then to Treasure Data is not recommended.
Read Cody Jannetti's full review
Johnny Kamel profile photo
October 30, 2017

TD Revew

Score 9 out of 10
Vetted Review
Verified User
Review Source
Treasure data is used by a select analysts and data engineers as the main ETL platform for event based data.

Our company includes two main sets of data, app analytics events logged when users interact with our apps and static data that is more business/inventory/finance focused.

Treasure data deals with the former (in correlation with the rest of the datasets that we house at our company) to aggregate and transform raw data into actionable usable tables
  • Connecting with other platforms. Love the connectors that TD offers and how easy they are to use
  • Scheduled queries are also very easy to manage and incorporate in workflos
  • TD UDFs are particularly handy and a great way to simplify code
  • Searching for past older jobs can be tedious sometimes. wish there was a more robust ability to search oder queries
Well suited for:
- workflow management
- aggregation an transformation layer

Not well suited for:
- Quick check queries
Read Johnny Kamel's full review
Sean Thompson profile photo
Score 10 out of 10
Vetted Review
Verified User
Review Source
We use Treasure data to collect and store information from all departments within the business, including web analytics, marketing spend, email activity, and customer engagement. The data is also used to build reports from board level reporting to day to day actionable reports for marketing, customer services, and product development. It helps us solve a range of data-driven problems across our whole business.
  • Easily stores a large amount of data - meaning you're not put off collecting things that may be useful in the future. We don't have to be conservative with what we store.
  • Connects to multiple data sources - so data generated outside platforms we control - like Facebook, Google Adwords - we can pull key data from these places too.
  • Quick querying - the query writing in Treasure data is helpful, they are also good UDFs that speed up and simplify queries.
  • We want to see our data, so to visualise it we need to use another tool on top, or export it.
  • At the moment, you can't search saved queries by the tables they use - I think it would be useful.
Treasure data is suitable for large-scale collection, storage, and analysis of information where users have a reasonable level of technical know how. If you're not capable of learning SQL, it would not be for you.
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Igor Pernek profile photo
Score 9 out of 10
Vetted Review
Verified User
Review Source
It is used as a data warehouse. Raw data containing operative business information is continuously ingested to Treasure Data. Different batch jobs are continuously running to aggregate data based on a different number of dimension to achieve relevant granularities for specific use cases. The data is used across the whole organisation for: reporting to customers, troubleshooting by tech support, analysis and feature design by R&D, etc.
  • Very reliable data ingestion to their warehouse
  • Fast querying capabilities using Presto and Hive
  • Good API for programatic access to the data
  • Adding support for not only batch processing but also streaming data
  • Better grouping and organization of saved queries and jobs
It is very well suited for use cases where the main requirement is to process store data in a scalable warehouse as a service and do batch processing of the data. It is less appropriate if the main business requirement is to be able to process streaming data in real time.
Read Igor Pernek's full review
Mike Galvin profile photo
Score 9 out of 10
Vetted Review
Verified User
Review Source
Shortening the time to market for getting data in the hands of users and easily integrating it into other platforms to centralize this data in a single place was a huge win for us. The ability to then query across data sets from different source systems at a large scale was great. The performance on very large data sets (billions of rows) was pretty good as well.
  • Very easy to get up to speed on the platform, the web interface was simple and easy to use and we were quickly able to leverage our teams existing SQL based skill set without having to know a ton about the underlying HDFS based platform Treasure Data sits on top of.
  • Speed of development was great and built-in connectors for various cloud data sources and destinations were excellent.
  • The ability to write directly to data sets for Tableau Online was a nice feature.
  • The workflow scheduling piece, while very robust was still too code/script heavy for what other integration platforms do easily in a simple UI. The UI will need to improve here to accommodate all the underlying features and functionality that can be implemented via the scripting language.
  • Updating data does not exist as part of the platform features so you just have to know what you want to use the platform for before implementation. This would be a nice feature enhancement.
It is very well suited when you have a need for a simple way to integrate both cloud and on premise software into a central data repository. Do not try to use this as a data warehouse replacement However, it could work nicely as a compliment to any data warehouse considering it's built in snapshot capabilities of all data by default. I was impressed with its "schema-less" design in which changes in upstream systems of source data don't break downstream integrations like many other platforms.
Read Mike Galvin's full review
Michael Yang Chen profile photo
Score 8 out of 10
Vetted Review
Verified User
Review Source
We have a huge amount of data that requires processing, and treasure data provides the big data solutions required to handle it all. We have hundreds of terabytes of data that needs aggregation and filtering before it is in a state that can be meaningfully used by our analysts to make business decisions.
  • Handles queries on big data well
  • Easy to use in conjunction with other data warehousing and data processing tools.
  • Web application often not responsive when the database grows to too large a size.
Good if you want to run big hive queries on gigabytes to terabytes of data. Good in conjunction with other data stores and data warehouses.

Not as good when you want your database to be easily accessible to your business analysts.
Read Michael Yang Chen's full review

About Arm Treasure Data

Arm Treasure Data manages customer data for global brands and Fortune 500 enterprises like Mattel, Subaru, Canon, LG and disruptive startups like Wish.com, Fivestars, and Zoom.
Categories:  Data Warehouse,  Customer Data

Arm Treasure Data Features

Arm Treasure Data Screenshots

Arm Treasure Data Videos (3)

Watch Transforming Your Digital Advertising With the Power of First Party Data

Watch Accelerating business operations with Treasure Data - featuring Kapost

Watch Data Stack Considerations - Build vs Buy at Tout

Arm Treasure Data Downloadables

Arm Treasure Data Integrations

Marketo, Segment, Mixpanel, Google Analytics, AppsFlyer, adjust, Amplitude Analytics, Chartio, Tableau Desktop, Tableau Server, Looker, Domo, Adobe Analytics, Heap, Hadoop, Amazon Redshift, App Annie, Microsoft Power BI, Tableau Online, Pentaho, Metric Insights, Microsoft Office 2016, Microsoft Azure, Google Cloud Storage, Google Drive, Intercom, Zendesk, Elasticsearch, MongoDB, Google BigQuery, Microsoft SQL Server, PostgreSQL, Snowflake, MySQL, MariaDB, Docker, Heroku Platform, Stripe, Mailchimp, Salesforce Marketing Cloud Email Studio, Oracle Eloqua, Pardot, HubSpot, Oracle Responsys, NetSuite, Facebook for Business, Sizmek, AdRoll, LiveRamp IdentityLink, Datorama, Twitter Ads, Google Tag Manager, Branch, Amazon Kinesis, Unity, TUNE (formerly HasOffers), Google Marketing Platform (formerly DoubleClick), salesforce sales cloud, kafka, hive mall, jupyter, pandas, R, mLab, fluentd, JDBC, Luigi, Python, Rest API, informatica, ruby, eyeota, instagram Ads, xbee, MQTT, RaspberryPi, Serial Devices, CSV, FTP, Webhooks, mysql workbench, razorSQL, SQuirreL SQL, iOS, Android, Unreal Engine

Arm Treasure Data Competitors

Pricing

Does not have featureFree Trial Available?No
Does not have featureFree or Freemium Version Available?No
Has featurePremium Consulting/Integration Services Available?Yes
Entry-level set up fee?No

Arm Treasure Data Customer Size Distribution

Consumers
0%
Small Businesses (1-50 employees)
0%
Mid-Size Companies (51-500 employees)
40%
Enterprises (> 500 employees)
60%

Arm Treasure Data Support Options

 Free VersionPaid Version
Forum/Community
FAQ/Knowledgebase
Social Media
Video Tutorials / Webinar
Phone
Live Chat
Email

Arm Treasure Data Technical Details

Deployment Types:SaaS
Operating Systems: Unspecified
Mobile Application:No
Supported Languages: English, Japanese