Toni Adams, SVP Partners & Alliances for Starburst, explored the critical shift toward “querying in place” to solve the 2026 data silo crisis. Starburst’s open hybrid platform serves as a federated engine that unifies data across on-premises legacy systems and fragmented multi-cloud environments without the need for expensive, time-consuming migrations. With over 50 enterprise-grade connectors and a robust governance layer, the platform is designed for highly regulated industries like finance and healthcare. Toni positioned Starburst not as a competitor to Snowflake or Databricks, but as a strategic orchestrator that treats these warehouses as data sources, allowing teams to enforce consistent, granular security policies—such as row- and column-level masking—even when exposing sensitive datasets to Large Language Models (LLMs).
Key 2026 innovations include an integrated Model Context Protocol (MCP) server and embedded vector search on Apache Iceberg, enabling AI agents to reason over structured enterprise data and unstructured vector stores simultaneously. For channel partners, this opens a vast landscape for advisory and managed services, supported by Starburst’s “Orbit” community and intensive technical bootcamps. By leveraging the platform’s conversational analytics agent to make data instantly actionable, partners can help clients move beyond static dashboards to a state of predictive, agentic intelligence—ensuring that AI initiatives remain secure, compliant, and vendor-neutral.
