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Starburst

Enterprise-grade distributed SQL query engine platform enabling fast, secure, and scalable analytics across multiple data sources.

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Product Overview

What is Starburst?

Starburst preview

Starburst is a high-performance data analytics platform built on Trino (formerly Presto SQL), designed to provide seamless, federated SQL query access across diverse data sources without the need for data movement. It offers a fully managed SaaS solution (Starburst Galaxy) and an enterprise distribution (Starburst Enterprise) that enhance Trino with advanced connectors, security, and management features. Starburst accelerates query performance, reduces infrastructure costs, and simplifies data access, empowering organizations to unlock real-time insights and support AI and analytics workloads at scale.


Key Features

  • High-Performance Query Engine

    Enhanced Trino engine with cost-based optimization, dynamic filtering, pushdown processing, and advanced caching to deliver fast and efficient queries on large, distributed datasets.

  • Federated Data Connectivity

    Over 40 enterprise-grade connectors enabling seamless SQL queries across diverse data sources such as Hadoop, S3, Snowflake, BigQuery, Kafka, and relational databases without data duplication.

  • Enterprise-Grade Security

    Comprehensive security features including end-to-end encryption, fine-grained access control, authentication options, and detailed auditing to ensure governance and compliance.

  • Flexible Deployment and Management

    Supports on-premises and cloud deployments with features like high availability, auto-scaling, monitoring dashboards, and simplified cluster management.

  • Fully Managed SaaS Option

    Starburst Galaxy offers a fully managed, enterprise-ready cloud service that handles infrastructure and configuration, enabling users to focus on analytics.

  • Cost Efficiency and Scalability

    Separation of compute and storage, optimized query execution, and reduced data movement lower infrastructure costs while scaling to support thousands of concurrent users and petabytes of data.


Use Cases

  • Real-Time Data Analytics : Accelerate insights by querying data in place across multiple sources, enabling faster decision-making without ETL overhead.
  • AI and Machine Learning Data Preparation : Enable data scientists to access and combine large, distributed datasets efficiently for training and experimentation.
  • Data Democratization and Collaboration : Provide secure, governed access to data across business units, breaking down silos and fostering data-driven culture.
  • Cost-Effective Data Lakehouse Architecture : Reduce reliance on expensive data warehouses by leveraging Starburst’s query engine to unify data lakes and multiple repositories.
  • Operational Analytics for Large Enterprises : Support complex, high-concurrency workloads in industries like finance, energy, and telecommunications with scalable and secure data access.

FAQs

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