Breaking the Streaming and Batch Silos
No more separation of streaming and batch pipelines. Unified ingestion and transformation in a single system.
Simplify Data Pipelines in One System
Unify stream and batch processing pipelines in just one architecture. Stream and process data at low latency exactly where your historical data is. Processing streaming data is as easy as writing a CTAS (Create Table As Select) SQL query — with Snowflake Dynamic Tables (public preview), customers can use simple, ubiquitous SQL to create low latency, incremental pipelines for an array of streaming use cases.
Optimize Cost Without Wasted Compute
Streaming ingest for rowsets is as much as 50% cheaper than file ingestion at the same volume. Dynamic Tables help you avoid wasted compute by providing performance guidance with incremental or full refresh for more efficient transformations.
Take Advantage of the AI Data Cloud
Since streaming capabilities are deeply integrated with the AI Data Cloud, you can still enjoy the security and governance capabilities you’ve come to rely on through Snowflake Horizon.
Stream Data with <10-Second Latency
Snowflake helps you handle both streaming and batch data ingestion and transformation in a single system.
Stream row-set data in near real time with single-digit latency using Snowpipe Streaming, or auto-ingest files with Snowpipe. Both options are serverless so you can scale more easily and manage costs more effectively.
Adjust Latency with a Single Parameter Change
With Dynamic Tables, you can use SQL or Python to declaratively define data transformations. Snowflake will manage the dependencies and automatically materialize results based on your freshness targets. Dynamic Tables only operate on data that has changed since the last refresh, making high data volumes and complex pipelines simpler and more cost-efficient.
Easily adapt to evolving business needs by making a batch pipeline into a streaming pipeline — with a single latency parameter change.
Snowflake is helping us fulfill our vision to centralize data and is quickly becoming our enterprise data platform across the city.”
Rohit Gupta
Chief Technology Officer, Department of Technology
City and County of San Francisco
50%
Faster data refresh operations with 18x more data.
300X
Faster data refresh in Tableau dashboards
Developer Resources
Follow along with Snowflake's Quickstart Tutorials or join an upcoming webinar to get up and running with Snowflake Dynamic Tables.
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