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We will the key advancements and AI-driven innovations within the Databricks Data Intelligence Platform as of late January 2026. The updates focus on unified management, AI agent extensibility, enhanced governance, and the seamless integration of transactional and analytical workloads. These releases emphasize usability improvements, security enhancements, and deeper AI capabilities, building upon the foundation laid in late 2025.
The introduction of the Lakebase App, accessible through the apps switcher in the Databricks UI, marks a significant improvement in usability. This unified interface consolidates the management of both Lakebase Provisioned and Lakebase Autoscaling instances, streamlining the previously cumbersome workflow that required navigating through the Compute tab in the Lakehouse UI.

Lakebase, Databricks’ fully managed PostgreSQL-compatible OLTP database, now offers a more intuitive project-based structure. This enhancement simplifies the process for developers and data teams to handle transactional data alongside analytics, eliminating the need for complex ETL pipelines. Billing for Lakebase Autoscaling commenced in January 2026, following a free exploration period in late 2025. Key features include autoscaling compute, scale-to-zero functionality, database branching, and instant restore capabilities.
Databricks Runtime 18.0, including its Machine Learning variant, achieved general availability in January 2026. This runtime, powered by Apache Spark 4.1.0 and utilizing JDK 21 as the default (an LTS release), incorporates a range of bug fixes, security patches, performance optimizations, and library upgrades.
Notable behavioral extensions include the application of time travel and VACUUM changes to serverless compute, Databricks SQL, and Unity Catalog managed tables across supported runtimes. These updates ensure consistent data management across diverse environments.
The AI/BI suite, which includes Genie (the conversational analytics tool), has received several usability enhancements designed to improve collaboration and efficiency:

Furthermore, Databricks Assistant now supports custom agent skills for domain-specific tasks in agent mode, adhering to the open Agent Skills standard. These skills load automatically when relevant, significantly extending the Assistant’s capabilities and making it more adaptable to specific business needs.
Knowledge Assistant became generally available in select US regions (for non-enhanced security workspaces), offering connectors for popular platforms like Google Analytics, Salesforce, and ServiceNow. Row filtering has been added to managed connectors, allowing users to ingest only the necessary data via SQL-like WHERE conditions, optimizing data transfer and storage.
Several updates have been implemented to enhance security, governance, and model serving capabilities:

The Data + AI Summit 2026 is scheduled for June 15–18 in San Francisco, and the call for proposals is already open. Major announcements are anticipated regarding AI agents, multi-model governance, and lakehouse expansions.
Meanwhile, legacy features such as Community Edition were retired on January 1, 2026, with users being directed to the perpetual Free Edition. Legacy dashboards have been fully phased out, encouraging teams to transition to modern AI/BI tools.
These updates collectively reflect Databricks’ ongoing commitment to building a more integrated, AI-native platform. The platform aims to empower data teams to build production-grade agents, unify OLTP and OLAP workloads, and provide business users with trustworthy insights, all while maintaining centralized governance through Unity Catalog.
For the most up-to-date details, please refer to the official Databricks release notes, as rollouts are staged across AWS, Azure, and GCP.