A data warehouse and lake all in one
Many enterprises use or will consider a data lake to store and analyze disparate data sources in their native form. This approach provides direct access to raw data as an alternative to storing varying data types in separate silos. However, data lakes, including those built on Hadoop, have struggled to deliver value because they involve significant complexity, require scarce programming skills, and lack critical data warehousing and SQL capabilities.
With Snowflake, you can cost-effectively store and process all of your diverse data – corporate data, weblogs, clickstreams, event data and email – all in one cloud-built platform. By design, Snowflake enables you to execute high-performance SQL queries on structured and semi-structured data to explore deeper data relationships. Build your data lake in the cloud with Snowflake.
Support all your data
Natively ingest semi-structured data (JSON, Avro, Parquet, and XML) from data sources, events, or applications without transforming it first. With Snowflake, you can integrate semi-structured data and query it with SQL.
Support all your users
Easily scale and allocate resources to different workgroups without data or resource contention, and take advantage of Snowflake’s elastic, automatic scaling to eliminate concurrency limits.
Support a multitude of use cases
From traditional data warehousing and business intelligence reporting, to data exploration and experimentation, Snowflake can handle diverse use cases with ease and simplicity.