The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.
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Treasure Data
Score 9.0 out of 10
Mid-Size Companies (51-1,000 employees)
Treasure Data is an enterprise customer data platform (CDP) that reclaims 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.
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Pricing
Snowflake
Treasure Data
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Snowflake
Treasure Data
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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More Pricing Information
Community Pulse
Snowflake
Treasure Data
Considered Both Products
Snowflake
Verified User
Engineer
Chose Snowflake
Our initial data warehousing solution was Treasure Data. We had issues with the costly pricing model, which would be exhorbitant if we want to hold our data in memory and query using Presto. As a result, some heavy lifting was done in Hive (managed by Treasure Data); …
Snowflake is cheaper, but TreasureData has a better interface and much more functionality. Also, TreasureData is able to process a greater number of records more efficiently. TreasureData has the ability to run both Hive and Presto. Also, TreasureData has native APIs for …
In terms of query speed and performance, Google BigQuery and Snowflake offer better performance at a lower cost. BigQuery's pricing on just the data scanned rather than cost of computation is far more attractive than Treasure Data's current model. We've selected Treasure Data …
Based on my experience, the most striking difference between the two platforms are the way their data models are organized. Agilone (now part of Acquia) has a very hard/strict requirement for integration with the source systems as we need to conform/adhere to their …
While Google BigQuery is an excellent data warehouse, it does not have all of the functionality of Treasure Data. Treasure Data's components make unifying and activating segments much easier.
Treasure Data stacks up very well against its competitors. It is a highly scalable tool with great support. The reason we went ahead with Treasure Data is that it has good customizations and AI capabilities. With machine learning and AI becoming more and more important every …
Treasure Data provides a combination of out of the box connectors, end to end functionality (Ingestion, Storage, Interactive Querying, Workflows and outputs all in one place) that no other solution we've found seems to do well. The fully managed nature of Workflow, combined …
Treasure Data is more cost effective than Leanplum, has more functionality then Mode or App Annie, although not as user-friendly or provides as many tools for analysis. As a data ingestion tool, Treasure Data we believe gave us the best bang for our buck. Our development …
This is where everything gets lost in translation. There is not a competitor that offers an end to end data services solution capable of managing etl , end-user adhoc usage, data delivery, warehousing, app sdk, WORKFLOW with digdag and so much more. Let’s not forget that all …
Snowflake is well suited when you have to store your data and you want easy scalability and increase or decrease the storage per your requirement. You can also control the computing cost, and if your computing cost is less than or equal to 10% of your storage cost, then you don't have to pay for computing, which makes it cost-effective as well.
Treasure Data is well suited to integrating multiple data sources, including online and digital sources. It is also well suited to trigger audience activations to known customers based on their online activity, integrating 3rd party data, and activating target audiences to ad platforms.
Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
Snowflake manages concurrency better in our trials than other premium competitors
Snowflake has little to no setup and ramp up time
Snowflake offers online training for various employee types
CDP provides a unified view of data from all touchpoints in the customer journey until a single customer uses the service. This feature is very helpful in making service decisions and direction.
It provides a variety of extensions to bring your data together in one place and helps you do this easily.
Kits provided by Treasure Box provide basic but helpful methods for further development of services.
Do not force customers to renew for same or higher amount to avoid loosing unused credits. Already paid credits should not expire (at least within a reasonable time frame), independent of renewal deal size.
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
I do think that we definitely will be renewing. We are putting major resources, time, and effort into Treasure Data becoming an extension of our organization, in many ways. We are working toward complete synergies with this product and leadership is very excited about the direction we are heading to be completely customer-centric.
Because the fact that you can query tons of data in a few seconds is incredible, it also gives you a lot of functions to format and transform data right in your query, which is ideal when building data models in BI tools like Power BI, it is available as a connector in the most used BI tools worldwide.
It's a easy platform to use and give the user detailed logs about what is going on in the workflows, so someone that do not have a lot of experience can start to work with it. And also the master segment usability is awesome, as we can filter a lot of data the way we want.
As treasure data has a 24 hours support, every time we has big issues that impacts the zones, we do have immediatly support from the treasure data team, so I would say that we do not have any issues with availability
Since treasure data has started having a huge amount of data, sometimes we do have problems with the workflows logs because we generate a lot of then. But with integrations I have not to complain, its really easy to integrate with other platforms.
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
The technical team has a good hold on the nuances of the data related to our organization. I have found the online technical support on their site quite responsive including the L1 support. In cases where the L1 team isn't able to resolve, I have found they are prompt in getting the product team's input to get a quick resolution.
I wasnt here at the training in the start, but I had a few training with treasure data for a few functionalities, and they provided me god explanations and great documentations, eve if the project were in beta.
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
We chose Treasure Data for the supreme customer service and lack of hidden costs. We don't need to manage any infrastructure or scale anything to meet customer demand. Treasure Data handles everything and makes it easy for us to integrate and focus on the tasks at hand. There may be cheaper options but we do not regret our decision to go with Treasure Data one bit.
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.