Cloud Data Warehouse

"snowflake data warehouse process"

Snowflake’s patented multi-cluster, shared data architecture can support any scale of data, workload, and users. Its ability to natively load and use SQL to query semi-structured and structured data within a single system simplifies your data engineering. With Snowflake’s near-zero management solution, one can focus on using data to drive insights instead of managing the overhead of a legacy data warehouse.

Traditional data warehouse solutions were not designed to handle the rapid growth in data and varying data types. They also were not designed to keep pace with the changing needs of end-users and the applications that rely on them. Only a data warehouse with a cloud-built data architecture makes it possible to support your current and future data analytics workloads at any scale.

With Snowflake, data is accessed through completely independent compute nodes that we call virtual warehouses. Each warehouse can scale up and down to match demand, even automatically. Crucially, any virtual warehouse can be automatically suspended or resized when peak usage has passed.

Consolidate Data Marts:

Take advantage of a modern architecture that brings together all your data in one place and makes it available to all your users and applications.

Handle any Scale of Data, Workload, and Users:

Deliver rapid insights at any scale without the complexity and headaches of traditional data warehouse or NoSQL solutions.

Support Modern Data and Applications:

Build and deploy innovative analytics solutions on top of a cloud data platform that can easily adapt to rapidly changing demands, in any region, on any cloud.