Snowflake Cloud Data Platform

Snowflake’s cloud data platform supports a multi-cloud strategy, including a cross-cloud approach to mix and match clouds as you see fit. Snowflake is available globally on AWS, Azure and Google Cloud Platform. With a common and interchangeable code base, Snowflake delivers advantages such as global data replication, which means you can move your data to any cloud in any region, without having to re-code your applications or learn new skills.

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Snowflake’s multi-tenant architecture enables governed and secure, modern data sharing in real time. Within minutes, and without ever having to move data, share any slice of your data across your organization or with any of your business partners and customers. With Snowflake’s Secure Data Sharing, you can easily forge one-to-one, one-to-many, and many-to-many data sharing relationships.

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Snowflake eliminates the administration and management demands of traditional platforms and big data solutions. Snowflake is a true data platform-as-a-service, running in the cloud. With built-in performance, there’s no infrastructure to manage or knobs to turn. Snowflake automatically handles infrastructure, optimization, availability, data protection, and more, so you can focus on using your data, not managing it.

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Per-second, usage-based pricing for compute and storage means you only pay for the amount of data you store and the amount of compute processing you use. Say goodbye to upfront costs, over-provisioned systems, or idle clusters unnecessarily consuming money.

Snowflake processes queries and tasks in a fraction of the time conventional on-premises and cloud data platforms require. Our columnar database engine uses advanced optimizations, including automatic clustering, which removes the headache of manually re-clustering data when loading new data into a table. Combined with the capacity to scale instantly and near-infinitely, you get the exact performance you need, exactly when you need it.

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You can rapidly integrate Snowflake with custom and packaged tools and applications. Our native and standards-based connectors, which include ODBC, JDBC, Javascript, Python, Spark, R, and Node.js, enable developers and tools that use a variety of languages and frameworks.

Snowflake can support all of your business data, whether from traditional sources or newer machine-generated sources, without requiring cumbersome transformations and tradeoffs. Snowflake’s patented technology natively loads and optimizes both structured and semi-structured data such as JSON, Avro, or XML and makes it available via SQL without sacrificing performance or flexibility.

Replicate data across cloud regions, across cloud providers, and keep data and apps where they are, while operating confidently with failover and business continuity.

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Snowflake’s unique architecture handles many database administration tasks for you. The services layer is constructed of stateless compute resources, running across multiple availability zones and utilizing a highly available, distributed metadata store for global state management. All operational states maintained within the services layer, which performs transaction coordination across all concurrent workloads, happens without impacting performance since each workload has its own, dedicated compute resources.

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Snowflake’s multi-cluster, shared data architecture is perfectly suited for any workload you can throw at it. See unmatched performance, scalability and concurrency for data warehousing. Work with data in your data lake and build robust data pipelines to streamline data engineering. Simplify and accelerate data science workloads with native integrations to leading languages such as Python, R and Apache Spark™. Or find new ways to profit from data using the Snowflake Data Exchange. Snowflake also provides builders and developers of data-driven applications and services a ready-made infrastructure and engine to build and run their solutions.

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Snowflake’s patented multi-cluster, shared data architecture separates storage and compute, making it possible to scale up and down, and on-the-fly, without downtime or disruption. Automatically scale to support any amount of data, workloads, and concurrent users and applications, without requiring data movement, data marts or data copies.