Retirement is planned for Azure in Oct 2026. Completed in other clouds in Oct 2025
Data residing in the Hive Metastore is opaque, suffers from low governance and is siloed in legacy technical constructs. The Hive Metastore (HMS) was a technology revolutionary in the Hadoop era, but it has become a bottleneck in the Lakehouse era.
Dark Data Silos: While the HMS model was valid for the batch processing era, it is a bottleneck in the Lakehouse & AI era. The major limitation is isolation. HMS is typically a workspace/cluster level resource leading to metastores operating as disconnected silos.
Access: HMS relies heavily on providing permissions at the broad level. Organizations are forced to rely on complex workarounds involving View based approaches or third-party security softwares just to handle multiple security areas leading to performance & management challenges.
RETL: RETL pipelines created to handle the last mile challenges are brittle jobs periodically copying data from HMS into PostgreSQL/MySQL solely to help an app read it.
AI: The primary driver for organizations today is Gen AI. Legacy HMS is fundamentally incapable of supporting the requirements of modern data platforms.
Organizations stuck on HMS are out of the revolution. They cannot deploy AI workflows due to the lack of a secure, governed store and the rich capabilities that modern platforms like Unity Catalog provide. Organizations must plan HMS migration to Unity Catalog at this stage
![Community [Industry BrickTalk #4] Transforming Commercial Real Estate Portfolio Management with AI](/t5/image/serverpage/image-id/25529iFB6AFAFAE433451D/image-size/large?v=v2&px=999)