First-party releases and research from Databricks. Headlines and excerpts link to the original articles.
California's Department of Health Care Services built its Behavioral Health Public County Profile on Databricks, per a Databricks account. The published details are limited to the headline and a short excerpt.
Databricks published an article arguing defense supply chains need governed data sharing across every tier. The excerpt offers no specific products, numbers, dates or customers.
Databricks has launched a public Beta of a Workday Data Connect federation connector for Unity Catalog. The connector lets Unity Catalog access Workday data without moving or copying it.
Databricks introduced Funke, a native HL7v2 parser for its lakehouse platform, addressing the messaging standard widely used in healthcare data exchange.
Databricks introduced Lakebase alongside an agentic software development lifecycle concept, pairing databases with branching to support coding agents. The company says AI has changed how software gets built as coding agents take on a growing share of the work.
Databricks and Replit have combined their platforms to let enterprises build governed applications, with Databricks Lakebase providing the data layer. The pairing is positioned as a complete development-to-deployment path.
Databricks published guidance on setting budgets and alerts to control cloud data warehouse costs, aimed at analytics teams facing surprise month-end invoices. The material is described as a response to a common scenario in which a single SQL query drives up spending.
Databricks announced the general availability of building permission-aware Databricks Apps with on-behalf-of-user authorization. Databricks Apps lets developers build and deploy data and AI applications directly on the Databricks platform.
Databricks published guidance on repointing existing dbt ETL pipelines to run on the Databricks Lakehouse, aimed at teams migrating their transformation workloads.
Databricks published a piece arguing that the lakehouse is a better data warehouse, citing 2026 benchmarks as proof and framing the warehouse as the right answer for 20 years.
Databricks published a talk abstract describing how IFCO, which runs one of the world's largest reusable packaging pools, scales and operates a large dbt project on Databricks, covering performance, visibility and debugging.
Meta's ads MCP server is now available on Databricks, according to a Databricks announcement. The integration is described as a way to use customer intelligence in advertising campaigns.
Databricks published an article titled "NEAREST BY Join: Scaling Vector Search in Databricks Runtime," describing vector search as originally a serving problem. The excerpt cites chatbots as the classical use case.
Databricks announced REGISTER and UNREGISTER APIs intended to prevent catalog lock-in and support data portability as organizations adopt lakehouse architecture.
Databricks published an article describing how Genie Ontology is used to power product development at the company. The available material only states that general-purpose AI agents are good at searching the web, reasoning, and writing code.
Databricks published a capital markets piece stating that on the buy side, net asset value (NAV) is the basis of operations, while the finance function protects the fee. The item carries a headline and an opening line only, with no specifics beyond that framing.
Databricks reports that more than 1 million Genie Agents were created in 2026 alone, and has published guidance on choosing a first Genie Agent for maximum impact.
Databricks published a post titled "Real-Time Retail Intelligence: Building E-Commerce Recommendations with Lakebase and AI Search on Databricks," about building e-commerce recommendation systems on its platform. Only the headline and a brief excerpt about personalization as a revenue engine were available.
Databricks published a piece describing how Genie One changes work for finance teams. The available item contains only a headline and a truncated excerpt, with no substantive detail.
Databricks described read restrictions and catalog labels as a way to unify governance across engines and catalogs, continuing its series on open table formats, open APIs and unified governance. No specific version, date, pricing or availability details were stated.