Starburst Galaxy's most valuable features include query federation, cluster management, and performance enhancements. Users highlight the ability to handle large jobs with right-sized clusters and support diverse data sources through a consistent interface. Cross-catalog querying, AWS Glue compatibility, and streamlined data connections boost user experience. Flexibility in connecting warehouses, compute-focused architecture, Iceberg support, autoscaling, and metadata management help reduce costs, optimize workload management, and facilitate integration with platforms like Kafka, S3 Iceberg, Snowflake, and Redshift.
- "Starburst Galaxy serves as our primary SQL-based data processing engine, a strategic decision driven by its seamless integration with our AWS cloud infrastructure and its ability to deliver high performance with low-latency responses."
- "Starburst Galaxy has improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."
- "Starburst Galaxy has improved our organization by unifying access to all major data sources, reducing the need for complex ETL processes."
Users desire improvements in Starburst Galaxy's cluster startup time, wishing for faster spin-ups and enhanced control over cluster configuration. There is interest in better Tableau and dbt integration, with more advanced connectors and documentation. They express a need for improved monitoring interfaces, alerting integrations, and support for more connectors like Kinesis and Firehose. Additionally, there is a call for greater observability, enhanced impersonation functionality for access control, and a Terraform provider for infrastructure-as-code workflows.
- "Cluster startup time is another pain point, typically 3 to 5 minutes, which is not the worst with proper planning but can be annoying for ad-hoc work."
- "Cluster startup time can be slow, sometimes taking over a minute."
- "The most persistent issue is the cluster spin-up time."
