Introducing Polaris Catalog

An open source catalog for Apache Iceberg


Snowflake for Data Engineering

Build powerful streaming and batch data pipelines in SQL or Python.

Simplify Complex Data Engineering Requirements

Build streaming and batch data pipelines on a single platform with the power of declarative pipelines and cost-efficient incremental refresh.  

Eliminate Unnecessary Pipelines With Data Sharing

Access live, ready-to-use data directly from thousands of data sets and apps via Snowflake Marketplace—all without having to build pipelines. 

Code With Your Language of Choice in One Optimized Engine

Program in Python, SQL and more, then execute with Snowflake’s multi-cluster compute. No separate infrastructure required. 

How It Works

Stream Data With <10-Second Latency

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.

Stream data with less than 10 second latency
Adjust latency with single parameter change

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 can operate only 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.

Power Data Engineering for Analytics, AI/ML and Applications

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. With Snowpark’s libraries and runtimes, this code can be in whichever language you prefer, including Python, Java or Scala.

Snowflake Platform
diagram showing code development in any IDE and code execution in Snowflake's engine

See 4.6x Faster Performance and 35% Cost Savings—Without Compromising Governance

Run Python and other programming code next to your data in Snowflake to build data pipelines. Automatically push down processing in multi-lingual runtimes built right into Snowflake’s elastic compute engine.


With the AI 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 Snowflake’s native connectors to bring data in frictionlessly, with no additional license cost. 

snowflake trail dashboard


Directly import project configurations and pipelines from Git, triggering deployments. Maintain database consistency with automated change management (create, alter, execute) into production environments. Manage Snowflake resources programmatically using Python APIs.* Automate tasks within your CI/CD pipeline (like GitHub Actions) with the Snowflake CLI. This empowers collaboration, version control and seamless integration directly on Snowflake or with your existing DevOps tools. And gain effortless observability with Snowflake Trail.


*In public preview


Break the Streaming and Batch Silos

Ingest and transform streaming and batch data in a single system.

leaders use snowflakefor data engineering

By migrating to Snowpark for their data engineering workload, Openstore now processes 20x more data while reducing operational burden and achieving 100% PySpark code parity.


Decrease in pipeline runtime


Reduction in engineering maintenance hours required

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Eliminate SiloedDevelopment

Bring more workloads, users and use cases directly to your data—all within the AI Data Cloud.


All the data engineering resources you need to build pipelines with Snowflake.

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Get up and running quickly with Snowflake tutorials for data engineering.

Virtual Hands on Labs

Virtual Hands-On Lab

Join an instructor-led, virtual hands-on lab to learn how to build data pipelines with Snowflake.

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Snowflake Community

Meet and learn from a global network of data practitioners in Snowflake’s community forum and Snowflake User Groups.

Start your 30-DayFree Trial

Try Snowflake free for 30 days and experience the AI Data Cloud that helps eliminate the complexity, cost and constraints inherent with other solutions.