Data engineering
The cloud data platform that made warehousing simple: storage and compute apart, almost no tuning.
Snowflake stores data centrally and starts separate “virtual warehouses” for each workload, so the finance reports never slow down the data science team. Most tuning happens automatically.
It is popular for SQL analytics and for sharing live data with partners without copying it. Python, ML and AI features (Snowpark, Cortex) bring more workloads next to the data.
Compressed, columnar storage managed for you.
Compute clusters you size, pause and resume.
Share live data with partners without copying it.
Python, ML and AI functions next to the data.
Typical ranges, not quotes. Scope, data and team size move them most.
The lakehouse platform from the creators of Apache Spark: data engineering, analytics and AI in one place.
Transformations written as tested, version-controlled SQL: software engineering for analytics.
The visual analytics pioneer, loved by analysts for fast, beautiful exploration.
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