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
Scoreย 8.7ย outย ofย 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
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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
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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); โฆ
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 โฆ
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 โฆ
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 โฆ
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 โฆ
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 โฆ
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 โฆ
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. Letโs not forget that all โฆ