Latest news with #StarburstGalaxy
Techday NZ
21-05-2025
- Business
- Techday NZ
Starburst rolls out AI features for unified data access
Starburst has announced a suite of new features across its Starburst Enterprise Platform and Starburst Galaxy aimed at unifying access to data for enterprise AI projects. The company's latest updates are designed to address challenges faced by organisations whose data is fragmented across on-premises, multi-cloud, and hybrid environments, making it harder to implement AI initiatives efficiently and securely. These capabilities are expected to help enterprises unlock modern data lakehouse architecture for AI applications, apps, and analytics. AI projects typically require integration across disparate systems, which can involve complicated pipelines and a lack of consistent governance. According to Starburst, this can slow experimentation, raise risks, and delay results due to difficulties accessing the correct data, involving stakeholders, and enforcing compliance policies. Justin Borgman, CEO and Co-Founder of Starburst, commented, "AI is raising the bar for enterprise data platforms, but most architectures aren't ready. At the end of the day, your AI is only as powerful as the data it can access. Starburst is removing the friction between data and AI by bringing distributed, hybrid data lakeside, enabling enterprise data teams to rapidly build AI, apps, agents, and analytics on a single, governed foundation." Among the significant updates is the introduction of Starburst AI Agent, a conversational natural language interface allowing data analysts and AI agents to generate insights directly from governed data within a secure Starburst environment. Starburst also rolled out AI Workflows, which streamline the process from experimentation to production for AI use cases by connecting vector-native search, context from metadata, and governance in an open data lakehouse architecture. Rob Strechay, Managing Director & Principal Analyst at theCUBE Research, said, "Starburst uniquely helps enterprises speed up AI adoption, reduce costs, and realise value faster by enabling access to all their data, no matter where it lives, across clouds, on-premises, or hybrid environments. The best part? Because data has gravity, they don't need to move or migrate it to build, train, or tune their AI models." Matt Fuller, VP of AI/ML Products at Starburst, stated, "We're turning the data lakehouse into an enterprise-grade platform for AI agents and applications - designed from the ground up to support air-gapped environments without compromising on flexibility. Whether deployed in a secure on-premise environment or cloud-enabled ecosystem, Starburst delivers federated, governed access, real-time context, and high performance query processing. We're not just accelerating AI innovation; we're operationalising it, securely and at scale." Additional functionality now available or in preview includes Galaxy's AI-powered Auto-Tagging, which uses large language models to detect sensitive data such as personally identifiable information (PII) at the column level. Human-in-the-loop review and support for custom classifiers are intended to strengthen governance and enable scalable Attribute-Based Access Control (ABAC) policies. Starburst has also released Starburst Data Catalogue, a new enterprise-grade metastore intended to replace Hive Metastore, with support for Apache Iceberg and future multi-engine integrations, aiming to reduce metadata sprawl and improve governance while avoiding vendor lock-in. Enhancements in data management show up in Galaxy's fully managed Iceberg Pipelines. This feature offers automated maintenance with options for streaming ingest from Kafka or batch ingestion from S3, and capabilities such as compaction and orphan file removal to ensure high performance and cost-efficiency for Iceberg tables. According to Starburst, this is designed to require no manual tuning from users. New tools like a Starburst-native ODBC driver and advanced features for Starburst Enterprise target query performance and operational efficiency, including scheduled materialised view refreshes and automated Iceberg table maintenance. Starburst is also offering automatic query routing in Galaxy, using load or user role to determine the appropriate cluster for each query, with the aim of improving performance and cost control. Starburst: Data-to-AI Readiness Blueprint is introducing a new service offering to help customers assess and improve their data infrastructure for future AI workloads. This engagement includes evaluating current architecture, streamlining integration across complex environments, and providing a tailored roadmap for data infrastructure for scalable and secure AI outcomes. Pedro Pereira, Staff Data Engineer at Going, commented, "Since choosing Starburst Galaxy as the core of our Lakehouse architecture, we've been using the built-in Streaming Ingest capability to land large volumes of flight and user the conclusion of our testing, we were left thoroughly impressed with the functionality, performance, and ease of use. Similarly, Galaxy Orphan File Removal exceeded our expectations by saving us an estimated USD $1,000/month in S3 storage costs..." Ricardo Cardante, Staff Engineer at TalkDesk, stated, "Before Starburst, maintaining our Iceberg tables was a manual, error-prone process that only covered a fraction of our data. With Automated Table Maintenance, we applied compaction and cleanup across the board, going from 16% table maintenance coverage to 100%. This enhancement led to a 66% reduction in S3 storage costs for our data platform buckets and contributed to an overall 20% decrease in S3 storage expenses across the company. It's a game changer for scaling Iceberg performance with minimal overhead." George Karapalidis, Director of Data at Checkatrade, said, "User Role-Based Routing in Galaxy made it simple to direct queries to the right cluster based on team roles. It's intuitive, seamlessly integrated into the Galaxy UX, and helps us optimise for both performance and cost without adding operational overhead."
Cision Canada
19-05-2025
- Business
- Cision Canada
Starburst Unveils New AI Platform Capabilities to Accelerate Enterprise AI and Agents
New innovations unify on-premises, hybrid, and multi-cloud data to power AI BOSTON, May 19, 2025 /CNW/ -- 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. "AI is raising the bar for enterprise data platforms, but most architectures aren't ready," said Justin Borgman, CEO and Co-Founder of Starburst. "At the end of the day, your AI is only as powerful as the data it can access. Starburst is removing the friction between data and AI by bringing distributed, hybrid data lakeside, enabling enterprise data teams to rapidly build AI, apps, agents, and analytics on a single, governed foundation." Introducing Starburst AI Agents: Unlock the Value of All Enterprise Data for Agent Intelligence "Starburst uniquely helps enterprises speed up AI adoption, reduce costs, and realize value faster by enabling access to all their data, no matter where it lives, across clouds, on-premises, or hybrid environments. The best part? Because data has gravity, they don't need to move or migrate it to build, train, or tune their AI models," said Rob Strechay, Managing Director & Principal Analyst, theCUBE Research. 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. "We're turning the data lakehouse into an enterprise-grade platform for AI agents and applications - designed from the ground up to support air-gapped environments without compromising on flexibility. Whether deployed in a secure on-premise environment or cloud-enabled ecosystem, Starburst delivers federated, governed access, real-time context, and high performance query processing," said Matt Fuller, VP of AI/ML Products, Starburst. "We're not just accelerating AI innovation; we're operationalizing it, securely and at scale." 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-Tagging simplifies 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 Inges t 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 Powering AI Innovations Across Industries According to Pedro Pereira, Staff Data Engineer, Going, "Since choosing Starburst Galaxy as the core of our Lakehouse architecture, we've been using the built-in Streaming Ingest capability to land large volumes of flight and user the conclusion of our testing, we were left thoroughly impressed with the functionality, performance, and ease of use. Similarly, Galaxy Orphan File Removal exceeded our expectations by saving us an estimated $1000/month in S3 storage costs..." According to Ricardo Cardante, Staff Engineer, TalkDesk, "Before Starburst, maintaining our Iceberg tables was a manual, error-prone process that only covered a fraction of our data. With Automated Table Maintenance, we applied compaction and cleanup across the board, going from 16% table maintenance coverage to 100%. This enhancement led to a 66% reduction in S3 storage costs for our data platform buckets and contributed to an overall 20% decrease in S3 storage expenses across the company. It's a game changer for scaling Iceberg performance with minimal overhead." George Karapalidis, Director of Data, Checkatrade, said, "User Role-Based Routing in Galaxy made it simple to direct queries to the right cluster based on team roles. It's intuitive, seamlessly integrated into the Galaxy UX, and helps us optimize for both performance and cost without adding operational overhead." 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. Supporting Resources About Starburst Starburst is the data platform built for flexibility, delivering fast, secure access to all your data, wherever it lives. Whether on-premises, across clouds, or in hybrid environments, Starburst provides choice and control to your architecture. Built on an open data stack with Trino and Apache Iceberg, it unifies distributed data without complex or costly migrations, unleashing the full power of the data lakehouse for analytics and AI. With our Lakeside AI architecture, enterprises gain federated access, governed collaboration, and full data lineage, laying the foundation for scalable, compliant AI innovation. Starburst empowers data-intensive and security-conscious organizations to unlock the full potential of their data while ensuring performance, governance, and control. Enterprises in 60+ countries, including Comcast, Citigroup, and 4 of the top 5 global banks, trust Starburst to maximize data value. Our strategic partnerships with AWS, Dell Technologies, and top cloud providers ensures seamless interoperability across environments. From insights to action to AI, Starburst fuels innovation at every level. Learn more at
