Snowflake’s Data Cloud is powered by an advanced data platform provided as Software-as-a-Service (SaaS). Snowflake enables data storage, processing, and analytic solutions that are faster, easier to use, and far more flexible than traditional offerings.

The Snowflake data platform is not built on any existing database technology or “big data” software platforms such as Hadoop. Instead, Snowflake combines a completely new SQL query engine with an innovative architecture natively designed for the cloud. To the user, Snowflake provides all of the functionality of an enterprise analytic database, along with many additional special features and unique capabilities.

Snowflake provides a single platform for data warehousing, data lakes, data engineering, data science, data application development, and secure sharing and consumption of real-time / shared data. Snowflake features out-of-the-box features like separation of storage and compute, on-the-fly scalable compute, data sharing, data cloning, and third-party tools support in order to handle the demanding needs of growing enterprises.

Benefits of Snowflake

• Instant, nearly unlimited scalability. Snowflake architecture uses a single elastic performance engine that delivers high speed and scalability. Snowflake supports as many concurrent users and workloads as you can throw at it, from interactive to batch. This powerful ability lies in its multi-cluster resource isolation. It’s high-performing and robust, giving enterprises the confidence they need that they’ll be able to handle every data workload. Snowflakes’ single engine powers everything from complex data pipelines, analytics, and feature engineering, to interactive applications across essential data workloads. With SQL query support and the Snowpark developer framework for Java and Scala access, Snowflake makes it easy for users with all skillset levels to leverage data.
• Automation made easy. Enterprises no longer have time for manual data management and maintenance; they must move fast and accurately. Automation makes this possible. Snowflake enables enterprises to automate data management, security, governance, availability, and data resiliency. This drives scalability, optimizes costs, reduces downtime, and helps improve operational efficiency. It’s built for high reliability and availability and it automates data replication for fast recovery.
• A single copy of data, shared securely, anywhere. Snowflake eliminates ETL and data silos, with seamless cross-cloud and cross-region connections and data sharing. Anyone who needs access to shared secure data can get a single copy via the data cloud, with the confidence that governance and compliance policies are in place. With a single shared data source, teams across the enterprise and the business’s ecosystem can be sure they are working from a single source of truth, making remote collaboration and decision-making fast and easy.
• Third-party data integrations.  Additionally, the Snowflake Data Marketplace offers third-party data and lets you connect with Snowflake customers to extend workflows with data services and third-party applications. 
• Performance and speed. The elastic nature of the cloud means if you want to load data faster, or run a high volume of queries, you can scale up your virtual warehouse to take advantage of extra compute resources. Afterward, you can scale down the virtual warehouse and pay for only the time you used.
• A data warehouse is a system designed to integrate big data sets from many sources, process it, and deliver analytical reports on demand. Business analysts and decision-makers can send queries and receive answers on the fly.
• Snowflake’s data warehouse is not built on an existing database or “big data” software platform such as Hadoop. Instead, it uses a new SQL database engine with a unique architecture designed for the cloud. Any software engineer with SQL experience can understand Snowflake and work with it.
• “Our goal was to deliver the analysis in less than 5 seconds. Thanks to Snowflake, we met it effortlessly. All the process – including sending the queries, downloading the data, and preparing visualizations – takes under 5 seconds.”