Snowflake vs Treasure Data: What are the differences?
What is Snowflake? The data warehouse built for the cloud. Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
What is Treasure Data? Flexible data analytics infrastructure as a service. Treasure Data's Big Data as-a-Service cloud platform enables data-driven businesses to focus their precious development resources on their applications, not on mundane, time-consuming integration and operational tasks. The Treasure Data Cloud Data Warehouse service offers an affordable, quick-to-implement and easy-to-use big data option that does not require specialized IT resources, making big data analytics available to the mass market.
Snowflake and Treasure Data belong to "Big Data as a Service" category of the tech stack.
What is Snowflake?
What is Treasure Data?
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Why do developers choose Snowflake?
What are the cons of using Snowflake?
What are the cons of using Treasure Data?
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I use Google BigQuery because it makes is super easy to query and store data for analytics workloads. If you're using GCP, you're likely using BigQuery. However, running data viz tools directly connected to BigQuery will run pretty slow. They recently announced BI Engine which will hopefully compete well against big players like Snowflake when it comes to concurrency.
What's nice too is that it has SQL-based ML tools, and it has great GIS support!