Organizations struggle to efficiently query and analyze data distributed across diverse environments, including hybrid, on-premises, and multi-cloud deployments. Moving data to a centralized location for analysis is time-consuming, costly, and introduces security risks. Traditional data warehouses often lack the scalability and flexibility to handle the increasing volume and complexity of modern data.

Starburst provides a data analytics platform built on a distributed SQL query engine that enables organizations to access and analyze data where it resides, without requiring data movement. The platform supports querying data across various sources, including data lakes, cloud storage, and traditional databases, fostering a unified view of enterprise data. By leveraging a massively parallel processing (MPP) architecture, Starburst accelerates query performance and supports complex analytics workloads over exabytes of data. The platform offers enterprise-grade security, governance, and scalability, empowering data teams to derive insights faster and more efficiently while maintaining data sovereignty. Starburst's "Lakeside AI" offering brings AI to where the data resides, rather than requiring expensive data migrations. The platform allows organizations to process data where it resides, addressing the challenge of data centralization. Starburst’s new AI offering includes a conversational interface, AI workflows, and air-gapped deployment, democratizing AI for SQL developers and enabling secure data sharing.

Distributed SQL query engine based on enhanced Trino

Support for querying data across hybrid, on-premises, and multi-cloud environments

Massively parallel processing (MPP) architecture for high-performance analytics

Connects to +50 data sources

Integration with Apache Iceberg for data lakehouse capabilities

Data Products architecture to curate, secure, and share data

Lakeside AI offering brings AI to where the data resides

Conversational interface, AI workflows, and air-gapped deployment

Role-based access control and data masking for enhanced security

Support for Amazon S3 Tables

The primary target audience includes data engineers, data scientists, data analysts, and other data professionals within enterprises seeking to unlock the value of their distributed data assets for analytics and AI initiatives.

Starburst offers both fully managed cloud (Starburst Galaxy) and self-managed (Starburst Enterprise) deployment options with pricing based on consumption and features.