The IT Nerd

 Starburst, the data platform for apps and AI, today announced a comprehensive set of product innovations across its flagship offerings: Starburst Enterprise Platform and Starburst Galaxy. The new Starburst AI Agent and new AI Workflows are designed to accelerate enterprise AI initiatives and support the transition to a future-ready data architecture built on a data lakehouse. By bringing distributed, hybrid data lakeside to power AI, apps and analytics, Starburst enables faster, more secure, and collaborative data access. With native AI tooling, the Starburst Data Catalog, and advancements to data ingestion, table maintenance and governance, enterprises can unlock the full power of the modern data lakehouse.

AI is pushing the limits of existing enterprise data architecture and most organizations are held back by fragmented data spread across clouds, formats, and teams. Building AI workflows often means stitching together brittle pipelines, coordinating across siloed tools, and managing sensitive data without consistent governance. Legacy architectures make it difficult to access the right data, involve the right stakeholders, and enforce the right policies: slowing experimentation, increasing risk, and delaying results.

Introducing Starburst AI Agents: Unlock the Value of All Enterprise Data for Agent Intelligence

At the heart of Starburst’s latest innovations is Starburst AI Workflows, a purpose-built suite of capabilities that speeds AI experimentation to production for enterprises. AI Workflows connect the dots between vector-native search, metadata-driven context, and robust governance, all on an open data lakehouse architecture. Starburst is also launching Starburst AI Agent, an out-of-the-box natural language interface for Starburst’s data platform that can be built and deployed by data analysts and application-layer AI agents to bring faster insights to business stakeholders. With AI Workflows and the Starburst AI Agent, enterprises can build and scale AI applications faster, with reliable performance, lower cost, and greater confidence in security, compliance and control. 

New Starburst Data and AI Innovations include: 

• Starburst AI Agent – A built-in conversational interface for governed natural language data product documentation and insight generation, in your secure Starburst environment. Availability: In Private Preview
• Starburst AI Workflows – With the introduction of Starburst AI Workflows, Starburst is addressing a key challenge in AI: unlocking governed, proprietary data fast enough to drive real outcomes. With AI Workflows, teams can search unstructured data, orchestrate prompts and tasks with SQL, and govern model access, delivered through the unified Starburst platform. AI Workflows combine AI Search to transform unstructured data into vector embeddings in Iceberg using your choice of embedding model, AI SQL Functions to run prompts and built-in LLM tasks from SQL, and AI Model Access Management to control usage and enforce governance – all without pipelines or data movement. Availability: In Private Preview
• Simplify AI Governance and Collaboration – Galaxy’s AI-Powered Auto-Taggingsimplifies governance by using LLMs to detect sensitive data like PII at the column level. With human-in-the-loop review and support for custom user-defined classifiers, teams can confidently scale ABAC policies and enable secure, self-service access to business users, without requiring manual policy enforcement. Availability: In General Availability
• Interoperability Without Lock-In: Starburst Data Catalog – Starburst also unveiled Starburst Data Catalog, a modern, enterprise-grade metastore solution purpose-built to replace Hive Metastore in Starburst Enterprise. With native Iceberg support, seamless Hive migration, and a flexible foundation for future multi-engine integration, it helps organizations reduce metadata sprawl, improve query performance, and simplify governance – without vendor lock-in. Availability: In Private Preview
• Fully Managed Iceberg Pipelines – Starburst Galaxy delivers a fully managed, end-to-end Icehouse lakehouse experience on Iceberg, combining automated maintenance and multiple ingestion options to simplify data readiness at scale. Built-in Live Table Maintenance with built-in maintenance features including compaction, snapshot cleanup, and orphan file removal to keep Iceberg tables performant and cost-efficient with no manual tuning required. Customers can choose between Streaming Ingest for near real-time updates from Kafka or File Loader for batch-style loads from S3, all fully managed in Galaxy. File Loader Generally Available in July, Streaming Ingest and Live Table Maintenance Generally Available now
• Scale Iceberg Workloads – Starburst Galaxy now streamlines large-scale Iceberg operations with Automated Table Maintenance to manage compaction, cleanup, and retention across deployments, to reduce storage costs and improve query performance with minimal operational overhead. Native support for AWS S3 Table buckets unlocks high-performance querying on Amazon’s new auto-managed storage format, while Nanosecond Timestamp Type Support adds precision for time-sensitive analytics. Automated Table Maintenance is Generally Available; AWS S3 Tables and Iceberg Nanosecond Timestamp Type are in Public Preview.
• Faster, Reliable Query Performance with Starburst-Native ODBC – Starburst enhances analytics performance with a high-performance ODBC driver built for secure, scalable BI access across both Galaxy and Starburst Enterprise. By eliminating third-party dependencies, the Starburst-Native ODBC enables deeper integration with Trino’s spooling extension, OAuth authentication, and Tableau’s generic connector, and ships alongside Enhanced Power BI Support. Availability: Public Preview, GA in June
• Starburst Enterprise Gets Even Stronger – Iceberg Parity and Operational Simplicity – Starburst continues to deepen its commitment to advanced features on Starburst Enterprise with new Iceberg-powered capabilities, including Automated Table Maintenance, scheduled materialized view refreshes with Iceberg MV Automatic Refresh, and full support for Data Products on Iceberg – providing a streamlined path to a scalable, collaborative Iceberg lakehouse architecture suitable for AI workloads. Availability: Public Preview
• Drive Efficiency with Automatic Query Routing – Starburst Galaxy now routes queries to the right cluster based on load or user role, improving performance and simplifying access at scale. User Role-Based Routing directs queries to pre-configured clusters based on a user’s role, maximizing price-performance. Deployment Set Routing supports resilient, large-scale deployments by routing queries across a defined set of clusters – ideal for high concurrency and resilient workloads. User Role-Based Routing is Generally Available, Deployment Set Routing is Private Preview beginning May 30th.
• Starburst: Data-to-AI Readiness Blueprint –  A new services offering designed to help organizations align their data infrastructure with evolving AI strategies. This comprehensive engagement evaluates the readiness of existing data architecture, streamlines access and integration across hybrid and multi-cloud environments, and ensures robust security and governance to support scalable AI workloads. Customers receive a tailored solution roadmap, architecture blueprint, and data product design guidance—empowering them to build a future-proof, high-performance data foundation optimized for AI innovation and success. Availability: Now

Register for Starburst Launch Point | May 28 (Virtual)

Join Starburst on May 28th for a virtual event where the company will unveil its vision for AI and walk through several exciting new announcements to its platform for data apps and AI. Attendees will hear from CEO Justin Borgman, Starburst product leadership, customers, and data professionals as they share product innovations and insights.

Register for EMEA/NORAM

Register for APAC

This entry was posted on May 19, 2025 at 9:54 am and is filed under Commentary with tags Starburst. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.