Use Scala, Python, or Java along with familiar DataFrame constructs to build powerful pipelines, ML workflows, and apps.
Extend Snowflake with in-engine JavaScript, Python, Java, and SQL functions to perform custom calculations.
Work with transactional and analytical data together in a single data set. Supports fast single-row operations so transactional applications can be built directly on Snowflake. In private preview.
Make SQL calls to Snowflake programmatically, without the need for client drivers or external API management infrastructure.
Query data in cloud object stores for additional insights—without having to ingest that data.
Store data externally in an open format with the performance, governance, security, and ACID transactions of Snowflake. In private preview.
Call code that is executed outside of Snowflake without the need to export and reimport data.
Build and deploy applications natively in the Data Cloud and make them discoverable via the Snowflake Marketplace. In private preview.
Automate transforming and optimizing continuous data loads with Snowpipe. Streaming pipelines in private preview.
Automatically detect changes in data and schedule tasks to perform required transformations.
Scale compute and storage independently and cost-effectively.
Isolate workloads so they can run and scale concurrently without contending for resources.
Ingest and immediately query JSON, Parquet, Avro, ORC, and XML without defining schemas in advance.
Easily ingest and analyze PDF documents, audio files, images, and other raw arbitrary binary data.
Integrate easily with native clients and connectors including ODBC, JDBC, Node, Python, .NET, Go, PHP PDO, Spark, and Kafka.
Easily restore and analyze deleted or modified historical data without backups.
Quickly create sandboxes and develop pilots with live data while avoiding the cost of copying and moving data.
Share live data easily, without the need to build and maintain API integrations.
Protect your customer’s data with role-based access controls and data encryption at rest and in transit.
With Streamlit, customers can bring rapid Python development directly to their Snowflake data. Data scientists and machine learning engineers can build and share interactive data visualizations with a few lines of code, without having to learn front end development languages. Streamlit integration is in development. About Streamlit >
Get access to technical experts to design the right architecture for your application, work with support engineers who specialize in app development, and participate in joint marketing campaigns.
Build your startup in the Data Cloud and take
advantage of free Snowflake credits,
architectural design consultation, and
co-marketing opportunities.
