In this video learn how Snowflake allows you to build a modern data architecture with their leading cloud data platform that eliminates the complexity, cost and constraints inherent with other approaches. Available as a service on Microsoft Azure, Amazon Web Services (AWS) and Google Cloud, Snowflake eliminates architectural complexities so you can run many workloads with the elasticity, performance and scale required by the modern enterprise. Its architecture is what makes Snowflake unique. Built entirely from the ground up for the cloud, Snowflake's architecture is comprised of:
- Centralized storage - for virtually unlimited amounts of structured and semi-structured data;
- Multi-cluster compute - for running multiple workloads without resource contention;
- Cloud services - to automate common administration, security and database tasks;
- A cloud agnostic layer - to deliver a consistent experience across cloud regions and providers.
Its unique architecture makes snowflake applicable to a wide range of workloads including:
- Data engineering - by leveraging Snowflake's ability to streamline data ingestion and integration;
- As a data lake - by using Snowflake as a data lake or alongside an existing one;
- For data warehousing - with unlimited performance and concurrency;
- To streamline data science – simplifying and driving performance for complex workloads;
- For building data-intensive applications that require an analytics work-horse at their core;
- Streamlined data sharing between consumers and providers.
Thousands of companies are experiencing performance, scale and productivity gains with the Snowflake Cloud Data Platform. Snowflake has over 1 extabyte of data under management and hundreds of thousands of users execute hundreds of millions of workloads every day.
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