Uploaded July 2026 | Updated September 2026, 2 weeks ago

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Databricks recently announced LTAP: Lake Transactional/Analytical Processing.

LTAP does not try to force transactions and analytics into the same engine. Instead, it unifies them at the storage layer:

→ Lakebase and Postgres handle transactions
→ Lakehouse engines handle analytics
→ Both access one governed copy of data in open formats on object storage
→ Each compute layer scales independently
→ No CDC pipeline or second analytical copy to keep synchronized

A Postgres-compatible engine remains specialized for low-latency transactional workloads, while Lakehouse engines remain specialized for analytics, ML and AI.

Read the technical deep dive: databricks.com/blog/lakebase-ltap-rethinking-database-storage