CDOs, data platform leaders, and analytics architects at enterprises that run Databricks in the cloud but hold regulated, high-gravity, or operationally sensitive data on-premises — particularly in financial services, manufacturing, energy, and healthcare.
.svg)
Replication, dual ingestion, and selective sampling all result in Databricks operating on incomplete or stale data — the problem is not data movement itself, but the delay it introduces between data generation and insight.
AIStor embeds Delta Sharing natively into the storage platform, enabling Databricks to query on-premises Iceberg and Delta tables live through Unity Catalog — data never moves, governance boundaries never expand.
The business case compounds across four dimensions: faster insight, lower TCO from eliminated pipelines, reduced governance risk from fewer data copies, and expanded Databricks ROI as previously inaccessible on-premises data becomes part of the analytics estate.
.svg)
