How teams are building on Snowflake Postgres
The Snowflake Online Feature Store exemplifies the innovative ways companies around the globe are harnessing Snowflake Postgres to revolutionize their data strategies. Below are some notable use cases that highlight this transformation.
Operational store
Organizations are increasingly consolidating their fragmented database environments, phasing out outdated systems, and simplifying multivendor setups with Snowflake Postgres, all while avoiding the need for extensive code rewrites.
- Ericsson aggregates data from every customer network worldwide—including software versions, hardware, and licenses—enabling over a thousand applications ranging from AI to customer support. By migrating four legacy databases to Snowflake Postgres, they eliminated synchronization pipelines and achieved a remarkable 99% reduction in data processing time.
- SimCorp manages investment data that spans over four decades, processing thousands of concurrent transactional updates each minute while navigating complex workflow states and fine-grained locking. Their transition to Snowflake Postgres resulted in a tenfold increase in disk operation speeds compared to their previous Postgres setup.
Faster analytics
With Snowflake Postgres, fresh operational data is primed for analysis without the hidden costs associated with traditional ETL processes.
- Sigma Computing provides clients with real-time analytics on the most current transactional data, querying directly within Snowflake and eliminating the need for external systems or cumbersome pipeline infrastructure.
Modern AI and app development
Intelligent applications and agents require immediate access to up-to-date operational context. Snowflake Postgres is engineered to facilitate high-throughput transactions and extensive analytics concurrently on a unified platform.
- BlueCloud supports low-latency transactional workloads alongside analytics and AI, all on a single platform, which minimizes infrastructure overhead and accelerates client operations.
- Superblocks empowers developers to create full-stack enterprise applications utilizing Snowflake’s coding agent, Snowflake CoCo. By connecting directly to Snowflake Postgres, developers can leverage familiar SQL tools against live data without the need for pipelines.
Snowflake Postgres is faster and more reliable than Lakebase
When comparing managed Postgres offerings, the distinctions become particularly evident at scale. Snowflake Postgres distinguishes itself with benchmark performance that is approximately four times faster than Databricks Lakebase.1 It also boasts a 99.95% published uptime SLA, while Lakebase lacks a public SLA commitment.
Snowflake Postgres operates on Postgres 18, in contrast to Lakebase’s limitations with versions 16 or 17. Furthermore, it accommodates up to 64 TB of storage, significantly surpassing Lakebase’s 16 TB cap.
From an operational perspective, Snowflake Postgres simplifies management through in-place major version upgrades with minimal disruption, effectively avoiding the downtime often associated with such transitions. Additionally, it supports standard logical replication, providing organizations with enhanced flexibility for data movement, migration, and integration—capabilities that Lakebase does not offer.
These features collectively position Snowflake Postgres as an optimal choice for enterprises seeking superior Postgres performance, scalability, and resilience.
Get started
Snowflake Postgres is production-ready and available today, while the Snowflake Online Feature Store is currently in public preview. Explore these resources to embark on your journey:
Forward-looking statements: This article contains forward-looking statements regarding our future product offerings, which are not commitments to deliver any specific products. Actual results and offerings may vary and are subject to known and unknown risks and uncertainties. For more information, please refer to our latest 10-Q.
Performance comparisons are based on internal benchmarks conducted in April 2026. Actual results may vary depending on workload, configuration, and region.
1 Based on PostgreSQL transactions per minute, comparing Snowflake Postgres HIGHMEM_4XL (96 WH) with Databricks Lakebase 64 CU (96 WH).
