{"id":33494,"date":"2021-11-12T08:33:37","date_gmt":"2021-11-12T13:33:37","guid":{"rendered":"https:\/\/centricconsulting.com\/?p=33494"},"modified":"2022-08-05T12:51:55","modified_gmt":"2022-08-05T16:51:55","slug":"how-snowflake-architecture-delivers-a-modern-data-storage-solution","status":"publish","type":"post","link":"https:\/\/centricconsulting.com\/blog\/how-snowflake-architecture-delivers-a-modern-data-storage-solution\/","title":{"rendered":"How Snowflake Architecture Delivers a Modern Data Storage Solution"},"content":{"rendered":"
The modern era\u2019s changing data needs are putting great strain on traditional data storage solutions. Built on the infrastructure-as-a-service (IaaS) model, these solutions are unable to handle the increasing diverse formats and greater quantity of data that users constantly generate.<\/p>\n
However, business needs have changed, too. New business requirements demand more than big data<\/a> infrastructure\u2019s ability to handle larger volumes of data. Business users need modern data storage solutions that allow them to process, categorize and retrieve data in near real time to meet consumers\u2019 needs for options, rapid access and more.<\/strong><\/p>\n In short, while traditional data storage solutions deliver many benefits, they also suffer from:<\/p>\n As a result, instead of more or bigger data warehouses, data managers today need cloud-based data storage solutions that enable diverse data-management architectures. That way, you can spend your time managing and fine-tuning data, rather than worrying about your infrastructure setups, node failures, security, day-to-day maintenance, and bad results \u2014 while meeting your business\u2019s data needs.<\/p>\n In 2019, Gartner released its report, \u201cMagic Quadrant for Data Management Solutions for Analytics<\/a>,\u201d announcing a solution called Snowflake<\/a> had emerged as a market leader. According to the report, the number of Snowflake customers tripled in 2018, fueling 247 percent year-over-year revenue growth.<\/strong><\/p>\n Gartner\u2019s report was an eye-opener that caught the imagination of the world. What made Snowflake\u2019s data storage solution so successful? Let\u2019s take a deeper look into the Snowflake architecture to find out.<\/p>\n One key to Snowflake\u2019s success is its multiple purposes: data lake, operational data store, data warehouse, and data mart. With increasing demand, people need a data architecture<\/a> or solution that is more:<\/p>\n Furthermore, Snowflake\u2019s platform enables enterprises to fully automate core business processes by:<\/p>\n However, Snowflake\u2019s cloud solution goes beyond elasticity because it is cloud agnostic. Whether data is stored in Amazon Web Services<\/a> (AWS), Azure or some other cloud solution<\/a>, Snowflake can manage it in multiple clouds. That gives Snowflake an added edge over its competitors.<\/p>\n Let\u2019s delve deeper and look at Snowflake\u2019s architecture.<\/p>\n Snowflake supports a high-level architecture, as depicted in the below diagram. It has three main components, which together make up the Snowflake data warehouse:<\/p>\n\n
Why Snowflake?<\/h2>\n
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Inside Snowflake Architecture \u2013 High Level<\/h2>\n