Starburst

Starburst is a Trino-based data lakehouse and federated analytics platform that lets organizations query, govern, and analyze data across object storage, databases, warehouses, and other sources without requiring all data to be centralized first. It is available as the fully managed Starburst Galaxy service and the self-managed Starburst Enterprise platform.

1. Analytics role: federated SQL queries can access and join data across multiple sources in a single query, while Starburst adds enterprise governance, workload management, and performance capabilities around Trino. Galaxy manages the underlying service in the cloud, whereas Starburst Enterprise can run across cloud, hybrid, on-premises, and Kubernetes environments.
2. AI capabilities: Starburst AI supports LLM functions, embeddings, and retrieval-augmented generation workflows. AIDA, now generally available, converts natural-language questions into SQL and analyzes governed data products conversationally. Galaxy also provides an MCP server that lets compatible AI assistants discover permitted data and execute read-only queries, although MCP remains public preview as of August 2026.
3. Implementation checks: buyers should assess connector coverage, Trino and SQL expertise, access-control requirements, query performance, network architecture, deployment model, and whether federation is preferable to moving selected datasets into a centralized lakehouse. For AI workloads, teams should also review supported model integrations, privileges, and MCP restrictions.
4. Commercial considerations: Starburst Galaxy offers Free, Pro, Enterprise, and Mission-Critical tiers. Pro starts at $0.50 per credit, Enterprise at $0.75, and Mission-Critical at $1.00, although actual credit prices vary by cloud provider and region. AIDA is included in applicable higher-tier configurations, with its token usage billed separately from Galaxy compute.

Starburst is particularly relevant to organizations that want governed analytics and AI access across distributed data while avoiding mandatory consolidation of every source into a single data platform.