DATABRICKS
DATABRICKS
Breaking down walls between data systems To get there, Databricks is pushing hard into a new category – lakebase architecture – and its product Databricks Lakebase Postgres. Understanding what that means requires a brief detour into how enterprise data has traditionally been managed.
For decades, businesses have operated two separate kinds of data systems. Analytical systems – used for insight and reporting – differ from operational systems, which handle transactions, orders and live workflows. Moving data between them has always meant creating copies, which quickly fall out of sync.
Shiv argues that this model is no longer fit for purpose, particularly as AI agents that can act autonomously begin to shoulder more of the work that people once did.
“ That world of taking extracts from the analytical world into the operational world accepts that humans will be doing work on spreadsheets,” Shiv continues.“ Agents, unfortunately, don’ t work like humans.”
Lakebase, as Databricks conceives it, dissolves the barrier between these two worlds. It allows predictive and generative AI outputs to be acted upon directly within live operational workflows, without the need for data extracts or manual intervention. Shiv draws on his background in aerospace to illustrate the point.
DATABRICKS
HEADQUARTERS: SAN FRANCISCO NUMBER OF EMPLOYEES: 10,000 FOUNDED: 2013 CEO: ALI GHODSI
Founded in 2013, Databricks is trusted by more than 20,000 customers, including 70 % of the Fortune 500. Its technology unifies structured and unstructured data under a single platform.
When working on aircraft predictive maintenance, his team could identify a likely failure in advance, but the next steps – checking parts availability and scheduling engineers – required querying entirely separate systems.
He adds:“ That part has become a lot easier now with Lakebase, versus having to manage the multiple data extracts from business systems.”
58 June 2026