
Build powerful streaming and batch data pipelines in SQL or Python.
Build streaming and batch data pipelines on a single platform with the power of declarative pipelines and cost-efficient incremental refresh.
Access live, ready-to-use data directly from thousands of data sets and apps via Snowflake Marketplace—all without having to build pipelines.
Program in Python, SQL and more, then execute with Snowflake’s multi-cluster compute. No separate infrastructure required.
Often kept separate, streaming and batch systems are typically complex to manage and costly to scale. But Snowflake keeps things simple by handling 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 for better scalability and cost-efficiency.
With Dynamic Tables (in public preview), 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 to make high data volumes and complex pipelines simpler and more cost-efficient.
As business needs change, you can easily adapt by making a batch pipeline into a streaming pipeline with a single latency parameter change.
Bring your workloads to the data to streamline pipeline architecture and eliminate the need for separate infrastructure.
Bring your code to the data to fuel a variety of business needs—from accelerating analytics to building apps to unleashing the power of generative AI and LLMs. Thanks to Snowpark, this code can be in whichever language you prefer, whether that’s SQL, Python, Java or Scala.
Code with Python, Java or Scala using Snowpark’s set of libraries, such as DataFrame API, and runtimes, including UDFs and stored procedures. Then securely deploy and process your code where your data is—all with consistent governance in Snowflake.
With Snowpark, customers see a median of 3.5x faster performance and 34% lower cost compared to managed Spark solutions.1
With the Data Cloud, you’ll have a vast network of data and applications at your fingertips.
Easily access and distribute data and applications with direct access to live data sets from Snowflake Marketplace, which reduces the costs and burden associated with traditional extract, transform and load (ETL) pipelines and API-based integrations. Or, simply use native connectors to bring data in.
Bring more workloads, users and use cases directly to your data—all within the Data Cloud.
All the data engineering resources you need to build pipelines with Snowflake.
Get up and running quickly with Snowflake tutorials for data engineering.
Join an instructor-led, virtual hands-on lab to learn how to build data pipelines with Snowflake.
Meet and learn from a global network of data practitioners in Snowflake’s community forum and Snowflake User Groups.
Try Snowflake free for 30 days and experience the Data Cloud that helps eliminate the complexity, cost and constraints inherent with other solutions.
1Data Source: Snowpark customer results