

Dremio and Starburst Galaxy are data platforms competing in the data management category. Based on user feedback, Starburst Galaxy has the upper hand due to its superior querying speed.
Features: Dremio is appreciated for its error handling, Apache Airflow integration, and efficient in-memory data operations using Arrow. It also manages data lineage and provenance, essential for compliance. Starburst Galaxy's strengths include a fast query engine and federated querying across multiple platforms like S3 and Redshift. Its compute-focused architecture and cross-database querying capabilities are beneficial for flexible tools and data integration workflows.
Room for Improvement: Dremio faces challenges with Delta connector support and limited documentation for complex use cases. There are performance drops during large queries and integration challenges with Databricks. Starburst Galaxy experiences lag in cluster spin-up times and lacks optimization for Tableau connectors. Enhanced documentation and observability features would improve user experience.
Ease of Deployment and Customer Service: Dremio supports hybrid and on-premises deployments but struggles to maintain integration with existing tools. While its support is commendable, it's limited by staffing constraints. Starburst Galaxy simplifies deployment due to its cloud-based nature but lacks advanced configuration control. Both platforms have commendable support but face challenges with vendor-specific issues.
Pricing and ROI: Dremio is known for cost-effectiveness, reducing manpower and simplifying infrastructure, though licensing costs for scaling can be significant. Starburst Galaxy offers a transparent pricing model with a predictable cost structure, focusing on cost-optimized configurations. Both platforms require careful consideration to optimize costs and benefits.
| Product | Mindshare (%) |
|---|---|
| Starburst Galaxy | 1.2% |
| Dremio | 2.4% |
| Other | 96.4% |

| Company Size | Count |
|---|---|
| Small Business | 1 |
| Midsize Enterprise | 5 |
| Large Enterprise | 5 |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 2 |
| Large Enterprise | 1 |
Dremio offers a comprehensive platform for data warehousing and data engineering, integrating seamlessly with data storage systems like Amazon S3 and Azure. Its main features include scalability, query federation, and data reflection.
Dremio's core strength lies in its ability to function as a robust data lake query engine and data warehousing solution. It facilitates the creation of complex queries with ease, thanks to its support for Apache Airflow and query federation across endpoints. Despite challenges with Delta connector support, complex query execution, and expensive licensing, users find it valuable for managing ad-hoc queries and financial data analytics. The platform aids in SQL table management and BI traffic visualization while reducing storage costs and resolving storage conflicts typical in traditional data warehouses.
What are Dremio's most valuable features?Dremio is primarily implemented in industries requiring extensive data engineering and analytics, including finance and technology. Companies use it for constructing data frameworks, efficiently processing financial analytics, and visualizing BI traffic. It acts as a viable alternative to AWS Glue and Apache Hive, integrating seamlessly with multiple databases, including Oracle and MySQL, offering robust solutions for data-driven strategies. Despite some challenges, its ability to reduce data storage costs and manage complex queries makes it a favorable choice among enterprise users.
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.
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.
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