Snowflake Postgres, Lakebase, HorizonDB: Picking the Lock-In You Want
Key takeaways
- In the last twelve months, three of the biggest data-platform companies have shipped a Postgres-flavored database with a custom storage layer and a scale-out compute, shared storage architecture.
- None of them is Postgres in the sense that matters to you.
- The honest first question is: what data platform are you already standardized on?
In the last twelve months, three of the biggest data-platform companies have shipped a Postgres-flavored database with a custom storage layer and a scale-out compute, shared storage architecture. Snowflake Postgres is GA, built on the Crunchy Data team s work, with pg_lake as the lakehouse hook. Databricks Lakebase is GA on AWS, public preview on Azure, built on the Neon engine plus the Mooncake integration work. Azure Horizon DB is in invite-only preview and is the most aggressive of the three architecturally — Microsoft built their own engine, claims up to 3,072 vCores and 128 TB databases, and benchmarks 3× the throughput of stock Postgres on OLTP.
All three are wire-compatible with Postgres. None of them is Postgres in the sense that matters to you. The question isn t which one is best — they re targeting overlapping but distinct workloads, and the meaningful answer depends on questions about your environment, not theirs.
The honest first question is: what data platform are you already standardized on? If your analytics warehouse is Snowflake, the answer is Snowflake Postgres or no managed cloud-native PG. If your analytics platform is Databricks, the answer is Lakebase or no managed cloud-native PG. If you re an Azure shop running on VMs and getting tired of it, the answer is HorizonDB or one of the others over private link with an asterisk attached.