Starburst Galaxy

Overview

Starburst Galaxy is a managed, cloud-hosted analytics platform built on Trino, designed to query data across sources without moving it. It suits teams that want federated SQL and lakehouse operations without managing complex data clusters. Its breadth of connectors and managed Iceberg maintenance are compelling, but usage-based charges make plan rates and billable activities central to budgeting.

Key features

Galaxy can query data lakes and warehouses together in one SQL query, avoiding a separate copy of the data for analysis. Starburst names more than 50 data sources, including Amazon S3, Snowflake, Redshift, BigQuery, and Azure Blob. That range makes Galaxy relevant when data is spread across those environments; teams needing a narrower or self-hosted tool may not need a managed federation layer.

Ingestion covers streaming from Kafka and batch loading of CSV, JSON, and AVRO into Iceberg. LakeOps automates Iceberg compaction, snapshot expiry, and orphan-file removal on a dedicated serverless engine, reducing routine table upkeep. AIDA converts natural-language questions into governed insights through a customizable interface or MCP; its token use is billed separately on Enterprise and Mission-Critical.

Security features include fine-grained RBAC and ABAC, end-to-end encryption, AI-powered data classification, and private connectivity. Starburst describes Galaxy as SOC 2 Type II certified and HIPAA-ready. Support professionals can be contacted from inside the product UI. Its REST API uses TLS/HTTPS, with authentication tokens that expire after 10 minutes.

Pricing

Galaxy uses freemium, usage-based pricing. The free plan is billed Free forever and includes up to three clusters, with standard execution mode for ad hoc queries. It is a practical starting point for limited exploratory work, but lacks the flexible execution modes and streaming ingestion included with Pro.

• Free: free, billed Free forever. Up to three clusters and standard execution mode for ad hoc queries.
• Pro: $0.50 per contact, billed Starting at $0.50/credit. Adds flexible cluster execution modes, streaming ingest, and advanced cluster management.
• Enterprise: $0.75 per contact, billed Starting at $0.75/credit. Adds advanced autoscaling, ABAC and SCIM, and AWS PrivateLink for data sources. AIDA token usage is billed separately.
• Mission-Critical: $1 per contact, billed Starting at $1.00/credit. Includes elite support, advanced governance integrations, and highest uptime guarantees. AIDA token usage is billed separately.

The 30-day free trial includes Enterprise features and $500 in Starburst Galaxy compute resources, giving teams a meaningful opportunity to evaluate higher-tier capabilities. Paid rates are starting points rather than a fixed total: rates depend on plan, and billable usage includes cluster compute hours, ingestion compute, and private-link data transfer. Account for those activities before estimating ongoing costs.

Platforms

Galaxy supports API, Linux, and web access, and is available on AWS, Google Cloud, and Microsoft Azure. Its cloud-hosted model is aimed at organizations that want managed analytics rather than responsibility for complex data clusters.

Who it's for

Galaxy is a strong fit for organizations consolidating SQL analytics across data lakes and warehouses, especially those adopting Iceberg or needing Kafka and batch ingestion alongside query federation. Starburst recommends it for organizations without the resources to manage complex data clusters. It is less suited to teams seeking a fixed-cost service: compute, ingestion, and private-link transfer are usage-billed, and higher-tier AIDA use adds a separate charge.

Pros and cons

• Pro: Federated SQL across more than 50 data sources avoids copying data just to query it.
• Pro: LakeOps automates several recurring Iceberg maintenance tasks on a dedicated serverless engine.
• Pro: The free tier and 30-day Enterprise-feature trial offer distinct ways to start, including $500 in trial compute resources.
• Con: Ongoing cost is tied to usage across cluster compute, ingestion, and private-link transfer, so the entry credit rate alone does not establish a total bill.
• Con: AIDA token use is separately billed on Enterprise and Mission-Critical, an extra cost to consider for teams relying on natural-language queries.

Alternatives

Choose Oracle Autonomous AI Lakehouse if an unlimited-time Always Free option subject to capacity limits better suits your starting point. Starburst Data Platform is another Starburst product with a free tier of up to three clusters and a Pro plan starting at $0.50/credit; compare it if you are considering the broader platform rather than Galaxy.

Amazon SageMaker Autopilot is a paid, pay-as-you-go alternative with no minimum fees or upfront commitments. Bauplan offers a free Sandbox with public datasets or uploads, full CLI, SDK, and API, and community Slack support, with everything public; consider it when that shared public environment fits your work.

Databricks Notebooks has a Free Edition with one serverless workspace and limited compute size and usage. IOMETE has a free self-hosted, on-premises plan capped at 100 vCPUs, for teams willing to operate in that model. Apache Hudi is a free open-source lakehouse platform with source releases and Maven artifacts.

Google Cloud Lakehouse for Apache Iceberg is a paid alternative with a metadata storage free tier that includes 1 GiB per month.

For broader comparisons, browse Data Lakehouse Platforms, Query Engine Software, Data Federation Software, and Data Virtualization Software.

Verdict

Choose Starburst Galaxy if your organization needs managed federated SQL across diverse data sources and wants ingestion and Iceberg maintenance in the same cloud-hosted service. Its strongest case is reducing the operational burden of a distributed analytics stack. Look elsewhere if cost predictability or self-hosting matters more: Galaxy's usage charges extend beyond its starting credit rate, and its model is managed cloud service.