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EmailStarburst Enterprise SEP 414-E+
End-to-end Iceberg analytics platform with comprehensive catalog support, full DML operations, enterprise governance, and advanced optimization features
Key Features
Comprehensive Catalog Support
Hive Metastore, AWS Glue, JDBC, REST, Nessie, Snowflake, and Starburst Galaxy managed metastore with flexible configuration via iceberg.catalog.type
Complete DML Operations
INSERT, UPDATE, DELETE, MERGE all supported with intelligent partition-aligned predicates and Iceberg v2 position/equality-delete files
Enterprise Security & Governance
Built-in access-control engine with table/column-level ACLs, LDAP/OAuth integration, and support for Lake Formation and HMS Ranger policies
Advanced Time Travel
Query past snapshots using FOR VERSION AS OF or FOR TIMESTAMP AS OF with metadata tables ($snapshots, $history, $manifests) and maintenance procedures
Adaptive Storage Strategies
Default copy-on-write for large rewrites with fine-grained updates creating separate delete files (MoR) merged at query time; handles position & equality deletes
Format Compatibility & Codecs
Supports Iceberg spec v1 & v2 with data files in Parquet (default), ORC, Avro and configurable codecs including SNAPPY, ZSTD, LZ4, GZIP
Performance Optimization Suite
Dynamic filtering, bucket-aware execution, metadata caching, automatic statistics, Warp Speed indexing, and materialized views for enterprise performance
Current Limitations & Roadmap
One catalog per config file; v3 preview only; manual optimization for frequent commits; some nested struct predicate limitations; streaming via external tools only
Starburst Iceberg Feature Matrix
Comprehensive breakdown of Iceberg capabilities in Starburst Enterprise SEP 414-E+
Dimension | Support Level | Implementation Details | Min Version |
|---|---|---|---|
Catalog Types | FullUniversal | Hive, Glue, JDBC, REST, Nessie, Snowflake, Galaxy managed metastore | 414-E+ |
Read & Write Operations | FullComplete | CREATE TABLE, CTAS, INSERT, and all query operations with atomic metadata swap | 414-E+ |
DML Operations | FullAll Operations | INSERT, UPDATE, DELETE, MERGE with intelligent partition-aligned predicates | 414-E+ |
MoR/CoW Storage | FullAdaptive | Default CoW for large rewrites; MoR for fine-grained updates with delete files | 414-E+ |
Time Travel | FullSQL Native | FOR VERSION/TIMESTAMP AS OF syntax with metadata tables and procedures. See time travel for details | 414-E+ |
Security & Governance | FullEnterprise | Built-in access control, table/column ACLs, LDAP/OAuth, Lake Formation, Ranger | 414-E+ |
Format Support | v1/v2Multi-Format | Iceberg v1 & v2, Parquet/ORC/Avro, configurable codecs (SNAPPY, ZSTD, LZ4, GZIP) | 414-E+ |
Performance Optimization | FullWarp Speed | Dynamic filtering, bucket execution, metadata caching, auto statistics, Warp Speed | 414-E+ |
Materialized Views | FullIncremental | Materialized views with incremental refresh for performance optimization | 414-E+ |
Streaming Support | NoneExternal Only | No built-in streaming; queries snapshots from external tools | N/A |
Iceberg v3 Support | PreviewRead-Only | v3 preview metadata reading under feature flag; production GA roadmap 2025 | 430+ |
Catalog Configuration | LimitedOne Per File | One catalog configuration per connector file; multiple connectors for multi-catalog | 414-E+ |
Showing 12 entries
For issues, click here (GitHub)Use Cases
Enterprise Data Warehousing
Comprehensive analytics platform with full DML capabilities and enterprise governance
- Real-world example: A Fortune 500 insurance company uses Starburst Enterprise to manage 100TB of policy and claims data across Iceberg tables. They use UPDATE operations to correct policy details, MERGE statements for claims processing, and materialized views to accelerate executive dashboards. Starburst's built-in access control ensures agents only see their assigned policies while executives get full visibility
- Large-scale data warehousing with complex transformations and ETL workflows
- Multi-tenant environments with strict security requirements and isolation
- Enterprise reporting and business intelligence platforms with advanced features
Multi-Cloud & Hybrid Analytics
Unified analytics across diverse catalog and storage environments
- Real-world example: A global logistics company has data in AWS Glue, Azure on-premises Hive Metastore, and GCP. Starburst connects to all three catalogs simultaneously, allowing analysts to write queries that join shipment data from AWS, customer data from on-premises Hive, and route optimization data from GCP - all in one SQL query without data movement
- Multi-cloud deployments with different catalog systems (Glue, Hive, Nessie, Snowflake)
- Hybrid on-premises and cloud data architectures during cloud migration
- Federation across multiple metadata and storage systems for unified access
High-Performance Analytics
Performance-critical workloads requiring sub-second response times
- Real-world example: A digital advertising platform uses Starburst with Warp Speed enabled to power real-time bidding dashboards. Queries that previously took 30 seconds now complete in under 2 seconds thanks to intelligent caching and indexing. The marketing team can analyze 500 million ad impressions interactively, adjusting campaigns based on live performance data
- Interactive business intelligence with large datasets requiring instant responses
- Real-time dashboards and operational analytics with SLA requirements
- Complex analytical queries with advanced optimizations (Warp Speed, materialized views)
Compliance & Audit Scenarios
Regulatory environments requiring comprehensive audit trails and access control
- Real-world example: A multinational bank uses Starburst for regulatory reporting with strict compliance requirements. They use [time travel](/blog/2025/10/03/iceberg-metadata/#63-time-travel-rollback-and-branching) queries to reconstruct account balances at specific points in time for audit purposes, column-level access control to protect PII data, and LDAP integration to ensure only authorized analysts can access sensitive financial data. All queries are logged for regulatory review
- Financial services regulatory reporting with detailed audit trails
- Healthcare data governance and compliance (HIPAA) with field-level security
- Data lineage and governance for compliance frameworks (GDPR, SOX, Basel III)