ABSTRACT: Starburst is redefining the AI data platform by enabling federated access to distributed data across clouds, on-premises, and hybrid environments, without requiring costly data movement. Its latest innovations, including AI Agents and AI Workflows, empower enterprises to build and scale AI applications directly at the lakehouse with built-in governance, vector-native search, and SQL-driven orchestration. By unifying performance, flexibility, and control, Starburst delivers a future-ready foundation for operationalizing AI where the data lives.
As enterprise AI adoption accelerates, data remains both the catalyst and the bottleneck. Most organizations grapple with fragmented data architectures, multiple data platforms, legacy systems, and many siloed environments spanning on-premises data centers, hybrid clouds, and multi-vendor storage platforms. Starburst aims to address this challenge by offering a federated, AI-optimized data platform built on an open lakehouse architecture.
“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.
With the latest release, Starburst expands this vision with native AI Agents, AI Workflows, and full support for Iceberg-based lakehouse operations across any environment. Starburst AI Workflows allow teams to orchestrate LLM tasks directly in SQL without data movement, delivering vector-native search, metadata-aware context, and prompt orchestration at scale. The AI Agent interface brings conversational insights to data products, bridging the gap between data teams and business stakeholders.
What we believe sets Starburst apart is its commitment to operationalizing AI at the lake, not forcing data migrations or lock-in proprietary formats. Through strategic partnerships, such as with Dell Technologies, Dell DataLake, and deep hybrid support, Starburst delivers governed, federated access and centralized policy enforcement across any data location. This simplifies architectural complexity and enables enterprises to scale AI workloads without compromising security or performance.
Starburst’s Data-to-AI Readiness Blueprint helps enterprises align data architecture with evolving AI strategies, ensuring Iceberg optimization, governance readiness, and workload portability. As AI innovation converges with the need for open, secure, and performant data access, Starburst offers an opinionated yet flexible foundation for building intelligent applications, RAG pipelines, and agentic AI services, wherever the data resides.
In addition, Starburst’s strategic investment from Citi underscores its growing momentum in regulated industries, enabling secure, governed AI and analytics at scale across complex, distributed data environments.
Our ANGLE
We believe that data platforms are more than storage arrays, and much more than just a DBMS. A data platform is much more than one or the other. We see it being much more. A data platform is a cohesive, scalable system that enables organizations to programmatically store, process, manage, and utilize data across a range of services and applications. It provides a unified environment where data can be ingested, transformed, queried, governed, visualized, and operationalized through layered technologies and integration protocols. In this data platform landscape, where enterprises can’t afford to copy or consolidate every dataset, we see Starburst delivering an essential alternative: AI at the lake, lakeside intelligence, and federated governance, operationalized at scale. This is a place we will be digging deep this summer in our Future of Data Platforms Summit by theCUBE Research.
