{"id":33568,"date":"2021-12-03T08:10:31","date_gmt":"2021-12-03T13:10:31","guid":{"rendered":"https:\/\/centricconsulting.com\/?p=33568"},"modified":"2022-08-05T12:55:55","modified_gmt":"2022-08-05T16:55:55","slug":"how-snowflake-architecture-delivers-a-modern-data-storage-solution-part-2","status":"publish","type":"post","link":"https:\/\/centricconsulting.com\/blog\/how-snowflake-architecture-delivers-a-modern-data-storage-solution-part-2\/","title":{"rendered":"How Snowflake Architecture Delivers a Modern Data Storage Solution, Part 2"},"content":{"rendered":"

In part one of this two-part series, we described how Snowflake can help you manage modern data-storage problems. Now, we\u2019ll take a deeper dive into the technical details.<\/h2>\n
\n

As I explained in my previous blog<\/a>, Snowflake works on a Storage and Compute separation model, which keeps the storage of data apart from its manipulation.<\/p>\n

Now I will explore the question: How does the storage mechanism interact with the compute engine?\u00a0To answer this question, let\u2019s start by exploring three ways Snowflake manages data.<\/p>\n

Managing Data With Snowflake<\/h2>\n

Storage<\/h3>\n

The persistent storage layer resides in a scalable cloud storage service, such as Amazon S3. This ensures data replication, scaling and availability without any management by customers. Snowflake optimizes and stores data in a columnar format within the storage layer, organized into databases as specified by the user.<\/strong><\/p>\n

PAX Architecture<\/h4>\n