الوصف
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: https://www.databricks.com/blog/lakebase-ltap-rethinking-database-storage