Starburst Galaxy offers rapid query speeds and robust cluster management, enhancing data engineering efficiency while supporting AWS integrations and cross-database functionality. Users benefit from its advanced data integration and federated querying capabilities.

| Product | Market Share (%) |
|---|---|
| Starburst Galaxy | 0.8% |
| Databricks | 12.3% |
| KNIME Business Hub | 11.2% |
| Other | 75.7% |
| Type | Title | Date | |
|---|---|---|---|
| Category | Data Science Platforms | Nov 1, 2025 | Download |
| Product | Reviews, tips, and advice from real users | Nov 1, 2025 | Download |
| Comparison | Starburst Galaxy vs Databricks | Nov 1, 2025 | Download |
| Comparison | Starburst Galaxy vs Amazon SageMaker | Nov 1, 2025 | Download |
| Comparison | Starburst Galaxy vs KNIME Business Hub | Nov 1, 2025 | Download |
| Title | Rating | Mindshare | Recommending | |
|---|---|---|---|---|
| Databricks | 4.1 | 12.3% | 96% | 91 interviewsAdd to research |
| Alteryx | 4.2 | 5.2% | 88% | 83 interviewsAdd to research |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 2 |
| Large Enterprise | 1 |
| Company Size | Count |
|---|---|
| Small Business | 32 |
| Midsize Enterprise | 24 |
| Large Enterprise | 83 |
Starburst Galaxy stands out with a compute-focused architecture that excels in facilitating seamless data integration. Technological innovations like autoscaling clusters and automated metadata management optimize operations in multi-tenant environments. With a keen emphasis on compatibility, the platform provides support for AWS Glue and enables federated querying across S3, Snowflake, and Redshift. This adaptability ensures comprehensive ETL processes and enhances analytics through querying SQL Server, Google Sheets, and blob stores. While noted for its robust capabilities, users seek improvements in cluster startup times, Tableau and AI support, and desire infrastructure-as-code enhancements.
What are Starburst Galaxy's key features?In industries focusing on large-scale data efforts, Starburst Galaxy plays an essential role in connecting data sources like Amazon S3 and RDS, streamlining tasks in data engineering and ad-hoc analysis across complex environments. Teams leverage its cross-database querying to boost AWS analytics, with features tailored for sectors needing agile data solutions, from ETL pipelines to secure data federation.
| Author info | Rating | Review Summary |
|---|---|---|
| VP, Business Intelligence at a outsourcing company with 501-1,000 employees | 5.0 | I use Starburst Galaxy on AWS to unify access across data sources like S3, Snowflake, and Redshift, reducing ETL complexity and enabling efficient analytics, though improved alerting, connector support, and query insights would enhance usability. |
| Sr Director, Technology at Spreetail | 5.0 | We've used Starburst Galaxy for six months to query data across diverse sources, reducing ETL time and storage costs. Its federated querying is powerful, though cluster startup can be slow. It's now central to our data operations. |
| Head of Engineering at a tech vendor with 1-10 employees | 5.0 | We use Starburst to manage large-scale data efficiently, improving performance and reducing costs by 25%. Setup was smooth, though cluster spin-up time and UI need work. Overall, it's enhanced our workflows and enabled a more cost-effective data strategy. |
| Head of Data at a financial services firm with 51-200 employees | 5.0 | I've used Starburst Galaxy for over three years to support fast, interactive queries and dashboards; it's more user-friendly and faster than alternatives like Databricks, though I wish it leveraged AI and had a broader ecosystem. |
| Chief Solutions Officer | 5.0 | I use Starburst to process large simulation datasets efficiently, benefiting from fast query performance, Iceberg table support, and secure access controls, though I'd like to see improved multi-tenant management across connected AWS accounts. |
| Chief Architecture Officer at a computer software company with 51-200 employees | 5.0 | I use Starburst Galaxy to efficiently connect and query data across sources, enabling integrated dashboards and reducing operational costs, though I’d like improved Tableau integration for cold starts and persistent connections during cluster startup. |
| Staff Analytics Engineer at a computer software company with 201-500 employees | 4.0 | We use Starburst Galaxy for flexible, cross-database querying and iceberg table management, benefiting from better performance and workload separation, though cluster startup delays and limited dbt integration are minor drawbacks compared to its overall adaptability and strength. |
| Engineering Manager | 5.0 | I've used Starburst Galaxy for nearly two years as our main SQL engine, benefiting from its AWS integration, low-latency performance, cost transparency, and features like autoscaling and metadata management, despite needing better impersonation for BI tools. |