Inside the Snowflake Elastic Data Warehouse

In this special technology white paper, Inside the Snowflake Elastic Data Warehouse, you’ll find out why today’s premises-based data warehouses are based on technology that is two decades old.  You’ll also discover why data warehouses have to fundamentally change in order to meet today’s demands and opportunities.

Addressing these limitations is not just a matter of adding a few more features to existing architectures—there are fundamental assumptions baked into current architectures that are no longer true. A redesign of the data warehouse is necessary. The paper explores – if we were to start over, unencumbered by the accumulated architectural baggage of data warehousing history, what would we build? The ideal data warehouse would combine the strengths of data warehousing—performance, security, and a broad ecosystem, with the flexibility and scalability of “big data” systems.

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Learn about Snowflake’s solution: a complete SQL data warehouse designed from the ground up as a software service that can take full advantage of cloud infrastructure. Snowflake’s data warehouse is, at its core, a massively parallel processing (MPP) database that is fully relational, ACID compliant, and processes standard SQL natively, without translation or simulation. Snowflake built their data warehouse service with a new architecture, one designed with the goal to deliver the best of data warehousing and big data solutions, but without the limitations of current architectures. Snowflake started with a fundamentally new architecture for data warehousing in order to deliver this elasticity, an architecture that physically separates but logically integrates storage and compute.

By reimagining and reinventing the data warehouse, Snowflake has addressed key limitations of today’s technology. Doing so required a new architecture, one that was not tied to the decades of data warehouse architectural history. As a result, users can focus on getting value out of their data without needing to spend significant time worrying about all of the tasks that are required with current data warehousing solutions. Rather than being bottle-necked waiting for the availability of overstretched IT and data scientist resources, analysts get rapid access to data in a service that can operate at any scale of data, users, and workloads.

The white paper includes the following high level topics:

  • The Need for Change
  • Reimagining the Data Warehouse
  • Snowflake: Elastic Data Warehouse as a Service
  • A New Architecture
  • Delivering Multidimensional Elasticity
  • Diverse Data, Without Compromise
  • Self-Managing Service
  • The Impact of Reinvention

The Inside the Snowflake Elastic Data Warehouse white paper is available for download in PDF from the insideAI News White Paper Library, courtesy of Snowflake Computing, Inc.