Databricks Launches LTAP: A Unified OLAP/OLTP Data Architecture
7 hours ago
- #Data Architecture
- #AI Integration
- #Real-Time Analytics
- Databricks introduced LTAP (Lake Transactional/Analytical Processing), a new architecture unifying OLAP and OLTP on a single copy of data in the lake.
- LTAP eliminates the need for ETL pipelines, replicas, and data movement, providing unified governance and a single source of truth.
- Powered by Lakebase, which adds Postgres-native transactions to object storage, LTAP supports independent scaling of transactional and analytical workloads.
- LTAP addresses limitations of previous approaches like HTAP and Zero ETL by unifying data at the storage layer using open standards like Iceberg and Delta.
- New Lakebase features include cross-cloud disaster recovery, git-style branching, snapshots, and autonomous database operations for enterprise AI at scale.
- LTAP integrates Lakebase and the Lakehouse through Unity Catalog, ensuring all data is governed and accessible without performance trade-offs.
- LTAP is designed for the AI and agentic era, enabling real-time data access for applications and agents without traditional infrastructure bottlenecks.