PUBLIC PREVIEW ANNOUNCEMENT
Snowpark
Use the language of your choice and familiar data frame constructs to build powerful and efficient pipelines and apps with the performance and ease of use of Snowflake’s processing engine.
Modern Data Engineering with Snowflake
Powerful and efficient pipelines thanks to the ease and performance of Snowflake.
Guide Book
Cloud Data Engineering For Dummies
Snowflake for your data engineering: performance, simplicity, and reliability.
Easily ingest, transform, and deliver all your data for faster, deeper insights. With Snowflake, data engineers can spend little to no time managing infrastructure, avoiding such tasks as capacity planning and concurrency handling. As a result, focus on high value-add activities towards delivering your data.
Your Data, Any Speed
With the Data Cloud, enable batch and continuous ingestion of structured and semi-structured data to ensure that virtually all data consumers operate on live data, accelerating data to insights.
Improve Pipeline Performance and Reliability
Run reliable pipelines thanks to dedicated, elastic, and right-sized computing resources for optimal performance and significant cost savings.
Reduce Pipeline Complexity
Bring extensibility to your pipelines. Leverage the data programmability of SQL, Snowpark, and functions to streamline pipeline development, with no additional clusters, services, or copies of your data to manage.
Learn more about Snowflake’s processing engine here.
PUBLIC PREVIEW ANNOUNCEMENT
How Snowflake Enables Modern Data Engineering
Batch and Continuous Data Pipelines for Various Data Formats
Modern data-driven applications can’t wait for data. Snowflake handles both batch and continuous data ingestion of structured and semi-structured data.
- Native support for semi-structured data with no need to define schema
- Automated and managed data ingestion in near-real time from cloud blob storage with Snowpipe
- Simplify change data capture (CDC) with Snowflake’s streams & tasks
- Easily load data and run with auto schema detection and instant data availability
Watch Webinar: Best Practices Delivering Continuous Data Pipeline >
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.
- Maintain performance across a near-infinite number of concurrent workloads thanks to Snowflake’s multi-cluster shared data architecture
- Process with Snowflake’s optimized data processing engine for data transformation workloads
- Only pay for what you use by optimizing pipeline performance and price, with instant resizing of dedicated compute clusters
- Scale a near-infinite amount of computing resources, up or down, with just a few clicks.
Simplified Data Transformation and Architecture
Streamline pipeline development and management with Snowflake, with less time spent on managing infrastructure and more time on delivering data.
- Collaborate and bring users together with different coding preferences thanks to Snowflake’s developer experience, Snowpark, and our native support for ANSI SQL.
- Extend your pipelines with Java functions (in public preview), external functions, JavaScript functions, and stored procedures.
- Build resilient data pipelines with schema-on-read and without the need to define schema in advance
- Enable your other data workloads with Snowflake – data warehousing, data lakes, data science, secure data sharing, and building and running data applications.
- Manage only one copy of your data to simplify data management and governance, and to improve DevOps and DataOps.
- Easily and securely share and consume live, governed data in real time.
Watch Webinar: New Features to Build Extensible Data Pipelines
“With Snowflake, we are operating over 100 data sets, and 400-500 jobs more than 10,000 times a day, with a 99.5% success rate.”
Mark Stange-Tregear
VP Analytics, Rakuten Rewards
“Snowflake has allowed us to shift our focus from putting out fires and solving problems to design and delivery of new insights.”
Michael Garlick
Director, Software Engineering, Xevo
Extensive Partner Ecosystem
Choose from an extensive ecosystem of data integration partners.
Resources
Explore other workloads
Data Lake
Improve data access, performance, and security with a modern data lake strategy.
Data Applications
Simplify developing data-intensive applications that scale cost-effectively and consistently deliver fast analytics.
Secure Data Sharing
Eliminate data silos and instantly and securely share governed data across your organization, and beyond
Data Science
Accelerate your data science workflows with access to more data, faster feature engineering, and direct integrations to leading ML tools.
Data Warehouse for Analytics
Enable everyone in your organization with fast access to a single source of data and eliminate the cost, complexity, and latency of your traditional data warehouse.