Powerful and reliable pipelines with the ease and performance of Snowflake.
Data Engineering for Performance, Simplicity and Reliability
Easily ingest, transform, and deliver your data for faster, deeper insights. With Snowflake, data engineers can spend little to no time managing infrastructure, avoid capacity planning and concurrency handling, and focus on building reliable, enterprise-ready data pipelines.
for Data Engineering
All Data at Speed With An Open Ecosystem
Collaborate in the Data Cloud with access to an open data ecosystem with streaming, batch, structured, and unstructured data, all in a single platform.
Performance and Reliability at Scale
Run enterprise-ready data pipelines with near-instant scalability and virtually no resource contention, powered by the elastic performance engine.
Radically Simple Data Pipelines
Simplify and eliminate unnecessary pipelines with intelligent infrastructure, pipeline automation, and data programmability.
ENABLES MODERN DATA
Batch and Streaming Data Pipelines with an Open Data Ecosystem
Modern data-driven applications can’t wait for data. Snowflake handles both batch and continuous data ingestion of structured, semi-structured, and unstructured data.
Performance at Scale with Tailored Transformation Needs
Traditional solutions require dedicated time windows for executing pipelines. On the flip side, Snowflake is uniquely architectured to provide multi-clustered computing, with resource isolation for each workload, in a secure and governed platform.
Simplified Data Transformation and Architecture
Streamline pipeline development and management with Snowflake, with less time spent on managing infrastructure, and no more unnecessary data pipelines.
Use Python, Java, or Scala, with familiar DataFrames and custom function support to build powerful and efficient pipelines, machine learning (ML) workflows, and applications. And gain the performance, ease of use, governance, and security that comes from working inside Snowflake's Data Cloud.
Snowpark will allow us to modernize and consolidate our data engineering pipelines, simplify our architecture with an easy transition from Spark, and allow our data engineering team to continue working with their preferred development interface, a DataFrame API with lazy evaluation, despite changing underlying platforms. This is a win-win, reducing time to insight for our customers while making processes easier and cheaper to manage for us.
IT Architect Director
We don’t need to go down the Spark road anymore because Snowflake is a scalable, reliable, and secure foundation for our advanced business intelligence and data science use cases.... Our Spark architecture wouldn’t have worked; it has to be Snowflake.
Director of Insights and Data Science
Key for us [is that] they allow our business partners to have both control of their data while making it accessible to others, without having to move it around and duplicate it, and have all the latency issues and duplication issues that come with that.... AT&T has data at our fingertips.
VP, Data Platforms
Choose from an extensive ecosystem of data integration partners.
Building with Snowflake
Find the resources you need to build apps, data pipelines, and ML workflows at the Snowflake Developer Center
Start Your 30-Day
Try Snowflake free for 30 days and experience the Data Cloud that helps eliminate the complexity, cost, and constraints inherent with other solutions. Available on all three major clouds, Snowflake supports a wide range of workloads, such as data warehousing, data lakes, and data science.
Eliminate data silos and instantly and securely share governed data across your organization, and beyond.