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Treasure Data has proven to be a versatile and powerful tool for a wide range of use cases. Customers have found that Treasure Data …
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What is Treasure Data?
Treasure Data is an enterprise customer data platform (CDP) that powers the entire business to reclaim customer-centricity in the age of the digital customer. It does this by connecting all data and uniting teams and systems into one customer data…
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What is Treasure Data?
Treasure Data is an enterprise customer data platform (CDP) that powers the entire business to reclaim customer-centricity in the age of the digital customer. It does this by connecting all data and uniting teams and systems into one customer data platform to power purposeful engagements that…
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What is Treasure Data?
Treasure Data is an enterprise customer data platform (CDP) that powers the entire business to reclaim customer-centricity in the age of the digital customer. It does this by connecting all data and uniting teams and systems into one customer data platform to power purposeful engagements that drive value and protect privacy for every customer, every time.
According to the vendor, Treasure Data serves customers globally across a broad base of industries that utilize it for personalization at scale:
• 170+ Pre-built connectors to collect data and activate profiles
• 2M+ Events collected every second
• 10B+M Profiles activated every month
• 130T Records managed
• 1M Presto queries run daily
• 30T+ Rows of data processed daily
• 99.99% Uptime
Treasure Data Screenshots
Treasure Data Videos
Webinar: What is a Customer Data Platform?
Watch How a Customer Data Platform Achieves Over 800% Marketing ROI
Watch Webinar: Demystifying Customer Data Platforms, with Winterberry Group
Treasure Data Integrations
- Adobe Marketo Engage
- Twilio Segment
- Mixpanel
- Google Analytics
- AppsFlyer
- Adjust by AppLovin
- Amplitude Analytics
- Chartio (discontinued)
- Tableau Desktop
- Tableau Server
- Looker
- Domo
- Adobe Analytics
- Heap
- Apache Hadoop
- Amazon Redshift
- data.ai
- Microsoft Power BI
- Tableau Cloud
- Pentaho
- Metric Insights
- Microsoft Office 2016 (discontinued)
- Microsoft Azure
- Google Cloud Storage
- Google Drive
- Intercom
- Zendesk Suite
- Elasticsearch
- MongoDB
- Google BigQuery
- Microsoft SQL Server
- PostgreSQL
- Snowflake
- MySQL
- MariaDB Platform
- Mirantis Kubernetes Engine
- Heroku Platform
- Stripe Payments
- Mailchimp
- Salesforce Marketing Cloud Email Studio, on marketing cloud
- Salesforce Marketing Cloud
- HubSpot Marketing Hub
- NetSuite ERP
- Meta Business Suite
- Sizmek Ad Suite
- AdRoll
- LiveRamp
- Salesforce Marketing Cloud Intelligence, on Marketing Cloud
- Twitter Ads
- Google Tag Manager
- Branch
- Amazon Kinesis
- Unity
- iOS
- Android
- Unreal Engine
- Oracle Marketing
- TUNE
- Google Marketing Platform
- pandas
- Eyeota
- Oracle Responsys
- part of Oracle CX Marketing
- salesforce sales cloud
- kafka
- hive mall
- jupyter
- R
- mLab
- fluentd
- JDBC
- Luigi
- Python
- Rest API
- informatica
- ruby
- instagram Ads
- xbee
- MQTT
- RaspberryPi
- Serial Devices
- CSV
- FTP
- Webhooks
- mysql workbench
- razorSQL
- SQuirreL SQL
Treasure Data Competitors
Treasure Data Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
| Supported Countries | global |
| Supported Languages | English, Japanese |
Treasure Data Downloadables
Frequently Asked Questions
Reviewers rate Support Rating highest, with a score of 8.2.
The most common users of Treasure Data are from Mid-sized Companies (51-1,000 employees).
Treasure Data Customer Size Distribution
| Consumers | 0% |
|---|---|
| Small Businesses (1-50 employees) | 10% |
| Mid-Size Companies (51-500 employees) | 50% |
| Enterprises (more than 500 employees) | 40% |
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Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Business Problems Solved
- Pros
- Cons
- Recommendations
Treasure Data has proven to be a versatile and powerful tool for a wide range of use cases. Customers have found that Treasure Data addresses the business problem of scattered data sources by providing a single platform for data collection and analysis. It serves as an ETL platform, analytical database, and data warehouse, supporting various business units across organizations. Users rely on Treasure Data as their primary storage and processing facility for large volumes of event data, eliminating the need to worry about storage and processing infrastructure.
Marketing teams utilize Treasure Data to enable a constant flow of data between databases and platforms like Salesforce, supporting email campaigns and providing refreshed data. The software helps clients understand customer behaviors, digitize the consumer base, and gain insights for business decisions, leading to increased revenue. It also serves as a central source of truth for customer data, solving the problem of fragmented information across digital and offline properties. Furthermore, Treasure Data is used for web tracking and analytics, supporting marketing teams in tracking website usage and campaign performance, ultimately improving the user experience. Overall, Treasure Data has helped companies store and secure their data while generating valuable insights to support data-driven decision-making.
Flexibility in Data Management: Many users have highly appreciated the flexibility of Treasure Data in ingesting different data sets and creating a data lake. This feature has been praised by numerous reviewers, allowing them to easily manage their data and streamline the data management process.
Extensive Native Integrations: The extensive native integrations provided by Treasure Data have received high praise from users. They have mentioned that these integrations cover the majority of systems they use, saving them time and effort in connecting different systems. Several reviewers have expressed their satisfaction with this feature.
Reliability and Uptime: Users consistently mention that Treasure Data is highly reliable, boasting a 99.99% uptime rate. This level of reliability has given them confidence in the platform and allowed them to trust that their data and jobs will always be accessible. Numerous reviewers have highlighted this aspect as one of the strengths of Treasure Data.
Cons:
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Frequent Request Failed Errors: Many users have experienced frequent "Request failed with status code 429" errors while using Treasure Data. These errors can be frustrating and disrupt the workflow, leading to delays in completing tasks.
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Lack of Error Resolution Guidance: Some reviewers have mentioned that they faced difficulties in resolving the "Request failed with status code 429" errors. They felt that there was a lack of clear guidance or documentation on how to troubleshoot and fix these issues, which made it challenging for them to resolve the errors independently.
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Impact on Productivity: The recurring "Request failed with status code 429" errors negatively impact productivity for some customers. Users expressed frustration at having to constantly deal with these errors, as it interrupts their work and requires them to spend additional time trying to resolve the issue or contacting support for assistance.
Users commonly recommend several actions for optimal use of Treasure Data. First, they suggest thoroughly testing the software before making a purchase decision. This allows customers to assess if the platform meets their specific needs and requirements. Second, users recommend having a skilled technical team in place to make the most of Treasure Data's capabilities. This ensures proper configuration and utilization of the platform's features. Lastly, users suggest engaging key personnel within the organization to maximize the benefits of using Treasure Data. This collaboration helps leverage the platform's flexibility and robustness for effective data management and analysis.
Additionally, users highly recommend Treasure Data for its comprehensive toolset, data connectors, analytical database, and excellent support. They emphasize that it is well-suited for managing massive amounts of data and allows analysts to work independently without relying heavily on engineers. With its powerful big data and business intelligence capabilities, Treasure Data can serve as an efficient ETL pipeline and facilitate seamless exporting of results to a warehousing database for scheduled queries. It is advised to ensure a comprehensive list of data sources and validate aggregation levels for accurate analysis. Reading through documentation and relying on customer success representatives are also recommended for efficient support.
Overall, users find Treasure Data to be a flexible and robust Customer Data Platform (CDP) with a powerful set of features and excellent support, making it a valuable asset for businesses dealing with large datasets.
Attribute Ratings
Reviews
(51-75 of 90)Companies can't remove reviews or game the system. Here's why
December 24, 2018
A great all-in-one tool for data management and unsiloe-ing
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 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 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.
August 04, 2018
Good product but can improve some functionality
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.
July 29, 2018
Make sure you give Treasure Data a try
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
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
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.
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.
Treasure Data 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 Treasure Data in the first place.
- Treasure Data is excellent in integration with various software and services.
- Implementation of the their SDK is also very easy.
- Treasure Data SDK works well in our applications and does not crush.
- Data management is very challenging with Treasure Data (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.
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.
- What Treasure 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.
November 01, 2017
Treasure Data: Data infrastructure as a Service
We are e-commerce startup without a data engineer. It's quite hard to find a good one and it also takes time to set up the infrastructure ourselves. However, the urgency of processing data is critical for us. We spend a lot on paid e-marketing and we need a way to measure the ROI daily.
Using Treasure Data, we started fast. We could track all user actions and which paid channel the users come from just by using Treasure Data's JS library. Since Treasure Data also has a connector to Postgres (our transaction DB), Facebook Ads, and Google Ads, data ingestion becomes much easier. Moreover, since Treasure Data already has a cron scheduler, we can easily run the queries (we have over hundreds Treasure Data queries) repetitively. The output is fed to Periscope data to be visualized and accessible across the organization any time. Now, all decision-makers in our company monitor the dashboard and make decisions based on it.
Yet, all that is done only by 2 data analyst and no data engineers.
- Data engineering as a service. It's like PaaS but for data infrastructure.
- Rich end-points. Almost all major services are connected to Treasure Data.
- Easy to use the web UI, yet feature rich.
- Pricing, a bit too expensive. Also hoping more flexible pricing plans
October 31, 2017
How much data can you handle?
Treasure Data is used by my organization to log lots of data points such as: events, device type, device OS, app version, and many others. Using the results we get from Treasure Data, our product owners are able to see what areas of the game people are using frequently and which areas they are not. Armed with this data we are able to make determinations of what features to include in other titles or what features may need some re-working. From the engineers incorporating Treasure Data into the game code to the Data Analysts decoding the data to the QA team making sure events fire when they are supposed to; Treasure Data is used widely across our game studio.
- Provides an immense amount of detail into customers and their uses of the application.
- Verification of the new features added into the products and if customers are using them or not.
- Provides a great tool for determining which bucket customers fall into while running an A/B Test
- Amount of time it takes to get data to populate columns after recently adding them to Treasure Data, could definitely be improved upon.
- A simple quick Query system that can be use by not programmers to quickly confirm data is being retained by Treasure Data.
October 30, 2017
TD Revew
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
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
October 27, 2017
Short Treasure Data Review
Treasure Data is used mostly by our analytics team in order to run large queries that would otherwise take a long time to execute. This drives insights into our users and A/B test ideas as well.
- Query optimization.
- Information flexibility.
- Querying language is slightly different than SQL and there are things that you don't have access to.
October 25, 2017
Treasure 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.
October 24, 2017
Treasure Data works well
Mainly storage of web pageview data, which we retrieve, filter and pull back into our own system. It's good, fast and easily queryable. We also use it for logging of application errors within our own dashboard and other interesting events that may occur, such as successful logins, etc. We've been able to query it via the JavaScript SDK for testing, verifying code/tag deployments.
- JavaScript SDK works very well
- Ease of creating new data structures easily
- Ease of user management - setting up specific queries for non-techincal users to access queries of interest.
- The javascript sdk returns data in jsonlines format when json is chosen, would prefer using actual json
- https://treasure-data.ideas.aha.io/ideas/SQL-I-107 - my request for a default sql statement when opening a table
- Speed, speed speed, we have about a 2-3 minute lag time between posting data and seeing it in the dashboard, there would always be room for improvement here
October 18, 2017
Reliable data warehouse as a service
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
October 17, 2017
Troves of treasure
Treasure Data is used for all of our server-side logging. We use it to debug issues that have arisen with our APIs and processes, as well as a way to collect data, which we then build into data pipelines to draw inferences about user behaviors.
- Scalability - we have so many tables, so much data and it's organized quite well. Easy to pull from various tables.
- The console is very clear and easy to use - makes onboarding easy, especially so for people that aren't as familiar with hive ql.
- Could provide a way to easily view or visualize metrics. We currently move data from Treasure Data to looker for this purpose - would be cool if there were business insight tools built in.
- Would be nice if there was search functionality in the console. Some simple wrappers around queries would be beneficial for operational people to look up the relevant data, rather than them needing to ask engineers to do a data pull for them.
October 09, 2017
Treasure Data is a great product!
We use Treasure Data across the whole company. For engineers, we use it to store important production logs, like request and response to a third party service. We also use it to store business data so that we can analyze user behavior...etc. Our fraud team and some other teams are also using the business data our engineers stored to generate all kinds of reports.
- It is easy to quickly check what the columns for a specific table are.
- It is easy to check all the previous queries I ran earlier so that I don't need to keep a record for myself.
- It is also easy to check other people's queries and it is easy to share your queries with others. My teammates shared several links like this with me, I found it is super helpful.
- It is pretty slow to load a database which includes lots of tables.
October 06, 2017
Treasure Data will Increase your productivity!
We use Treasure Data to ingest multiple data sources and once processed export them to Tableau dashboards.
One of our clients has data in more than 10 places (API, websites, local files), we use Python to gather all these sources and ingest them to Treasure Data. We also use Unity SDK and Unreal SDK to track user behavior in games.
After a processing passes we export the datasets to Tableau.
One of our clients has data in more than 10 places (API, websites, local files), we use Python to gather all these sources and ingest them to Treasure Data. We also use Unity SDK and Unreal SDK to track user behavior in games.
After a processing passes we export the datasets to Tableau.
- Treasure Data has a lot of connectors that allow for ingesting and exporting data easily.
- Treasure Data has a Python library to easily interface with TD SQL queries to Pandas DataFrames.
- Treasure Data has a very powerful workflow tool named DigDag that simplifies the multiple ETL processes we use.
- The website UI and especially the searching option of some queries should be improved. The user should be able to create labels to group queries.
October 06, 2017
Promising Tool for Data Analysis
We use Treasure Data extensively in the analytics team. As an analyst, I deal with data every day. Running those complex queries consumed a lot of my daily work time. But with Treasure Data's functions and support, I find it easy to run long and complex queries and export my results to any other platform like tableau.
I am particularly impressed with the active online support they provide. Any concerns with the tool and queries are very well addressed and answered.
I am particularly impressed with the active online support they provide. Any concerns with the tool and queries are very well addressed and answered.
- Online help/support
- In built functions for faster query operations
- Integration with other tools
- Auto select functionality was easier, they stopped suggestions being automatically selected
- Query optimizing tricks
October 06, 2017
Treasure Data for small businesses
Treasure Data has become our primary data store. It has the backbone of our data.
- Easy to use interface
- Very communicative on problems/service interruption
- Support staff is very quick and attentive
- A little costly
October 02, 2017
Treasure Data - definitely some hidden gems here
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.
September 29, 2017
Treasure Data - it's pretty good
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.
September 28, 2017
Treasure Data Enables Your Data Driven Org
Treasure Data is being used across the organization by analytics, engineering, and product management, with Analytics being the main user group. We use Treasure Data to query large data sets and complicated queries. Because Treasure Data can handle these much better than our current solution via parallel processing and table chunking.
- Very fast querying engine
- Easy for analysts to create their own customized tables with auto updates
- Can easily integrate with our BI tools
- Easier to access and start working on data
- Web based application so any device can access with credentials
- Keeping records of all queries ran
- Great customer support
- Presto syntax takes a little to get used to
- Some UDF takes time to get used to
- Smaller queries takes slightly longer than traditional SQL
- UIUX could improve. Make it easier for users to start new query, find jobs ran, etc.
September 28, 2017
A great tool for companies prior to big-data-tool deployment
Treasure Data (TD) is used across our company. We keep track of KPIs daily or study on analytical thesis using TD.
- Short running time compared to traditional databases.
- Better but not too complicated UI.
- Online chat is extremely helpful. There's always someone who can help improve the efficiency of you query.
- As an analyst, I don't have a comprehensive understanding of how to maintain and manage the tables. Sometimes not all the data is available in TD and we need to talk to engineers and have them import the tables we need.
- Syntax is a bit different and some TD specific functions are not very easy to get and learn.
September 27, 2017
Great platform to ingest large amounts of data with lots of easy to use integration points.
Treasure Data is used at the department level. It allows us to perform analytics on huge amounts of data. We load realtime data as well as very large batch files. It integrates really well with Amazon S3.
- Treasure Data provides a large portfolio of integration points, very easy to use and manage. Ingestion of data is easy, flexible.
- Treasure Data has really great support, whenever there is an issue they are quick at responding and fixing the problem, or guiding us to resolve the problems.
- Scalability is never an issue, ingestion of large amounts of data is so easy.
- Auditing could be improved. It is critical to know the metadata around the ingestion process.
September 27, 2017
Treasure Data Review
Treasure Data is being used as our analytics data layer. Most of our data analytics and reports are drawn from Treasure Data.
- Executing large queries is relatively quick and scalable
- Well integrated with other systems
- Indexing functionality is lacking
- Having a query plan or more detailed breakdown for queries would be nice