Snowflake for Data lakes
Build a governed, performant data lake that supports a variety of data sources and integrations to unify data for analytics, AI, apps, and more.
Gain value from your data, all in one platform
Seamlessly use unstructured, semi-structured and structured data together, whether it’s stored externally or in Snowflake’s optimized, managed storage.
Protect your data with built-in governance
Secure your data lake with granular access controls, and out-of-the-box telemetry to audit usage.
Lower Total Cost of Ownership With a Fully Managed Service
Spend less time and money keeping the lights on—and more on strategic work—by letting Snowflake handle upgrades, availability, storage maintenance, compliance certifications and more.
How it works
Unify data with fully managed, compressed storage
Reduce the complexity of stitching together multiple services and systems by supporting many use cases on unstructured, semi-structured and structured data — all in one platform.
With efficient compression, automatic micro-partitioning and encryption in transit and at rest, Snowflake’s fully managed storage helps spare you the hassle of securing, backing up and optimizing your data files.
Simplify access to data with integrated external storage
Manage and access files and tables stored in external data lake storage—including open file formats and Apache Iceberg—without having to copy or move data.
Easily integrate third-party data 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.
Know, protect and connect your data
Whether you’re storing data in Snowflake or your own object storage, you can use Snowflake Horizon Catalog to understand, govern and audit your data, apps and models.
- Detect and identify sensitive and PII data with Classification
- Monitor sensitive data for compliance, discovery, protection and resource usage with Object Tagging
- Enforce column-level security with Dynamic Data Masking and External Tokenization
- Automate masking policy enforcement with tag-based masking
- Enforce row-level security with Row Access Policies
- Use built-in, ready-to-query views to comply with regulatory auditing requirements and understand lineage, usage patterns and relationships
Code and process in your language of choice
Run pipelines with Snowflake’s elastic multi-cluster compute for reliable performance, cost savings and near-zero maintenance.
Ingest and transform files or tables with SQL, Python, Scala or Java — without the need for additional clusters, services or data copies to manage.
Save time and money on platform management
Snowflake’s near-instant elasticity rightsizes compute resources, and consumption-based pricing ensures you only pay for what you use. Ongoing performance improvements and native optimizations continue to make costs increasingly efficient.
our customers
leaders build data lakes with snowflake
"By taking advantage of the Snowflake virtual warehouse, we were able to meet our one-to-three-minute SLA for processing pipelines and bring down total runtimes by as much as 75%."
Mario Melendez
Director, Data Management and Analytics, AMN Healthcare
- $2.2 M Estimated annual savings
- 99.9% Pipeline success rate
Many Architectures In The AI Data Cloud
In addition to building data lakes, you can use the Snowflake platform for a variety of architecture patterns to best suit your needs—all globally connected in the AI Data Cloud.
Data Mesh
Deliver domain-driven ownership with self-service infrastructure as a platform.
Data Lakehouse
Build a transactional data lake architecture pattern for unified analytics, AI/ML and other collaborative workloads.
DATA LAKE QUICKSTARTS
Follow along with Snowflake’s Quickstart guides to learn hands-on how to work with data in semi-structured, unstructured, and open formats.
