Starburst Enterprise Delivers Incremental Iceberg Materialized Views, Query Speed improvements and Enhanced AI Intelligence

Today, we are excited to announce the release of Starburst Enterprise 482-e LTS. This release accelerates our ongoing commitment to open lakehouse standards, introduces native performance optimizations for materialized views, expands platform observability for AI, and delivers major connectivity gains across federated and time-series data sources.

Collectively, 482-e introduces significant improvements in the following areas:

• Icehouse Innovations:
  Scheduled, append-only incremental refreshes for Iceberg Materialized Views and Iceberg REST Catalog support with enhanced credentials in Starburst Metastore.
• Engine Performance & Query Optimization:
  10% faster query times based on internal benchmarking, lower latency, and support for PyStarburst Arrow protocol acceleration, and Queries Exceeding Ram to prevent Out of Memory (OOM) failures in public preview.
• Platform Intelligence & AIDA:
  Token consumption monitoring for AI administrators, broader OAuth capabilities for external Model Context Protocol (MCP) servers, and Data Product Enrichment v2.
• Expanded Open Connectivity:
  General Availability for the Great Lakes and OpenSearch connectors, alongside Public Preview support for OpenAPI and kdb+ connectors.

Icehouse advances with Incremental Materialized Views

Starburst continues to deepen its status as the ideal foundation for Apache Iceberg workloads. In 482-e LTS, we focus on eliminating the recompute overhead of precomputed data products and expanding catalog interoperability.

Incremental Iceberg Materialized Views 

Now available in public preview, Starburst Enterprise introduces incremental refreshes for append-only Iceberg materialized views. Previously, updating an Iceberg materialized view required a full re-execution over historical datasets, creating prohibitive refresh windows and heavy compute costs.

Administrators can now schedule append-only refreshes using an incremental_column across any Trino-queryable source, or define them directly through data products, without deploying a separate caching service. By processing only newly added rows, data engineers can drastically shorten refresh windows and remove a primary technical blocker when migrating legacy Hive pipelines to Apache Iceberg.

Open Iceberg REST Access for Starburst Metastore 

Now in public preview, Starburst Metastore (formerly Starburst Data Catalog) adds native support for the open Iceberg REST Catalog specification, complete with managed credentials, PAT-style tokens, and identity support for Okta and Ping Identity. Teams standardizing on the open Iceberg REST spec can now use Starburst Metastore as a unified catalog across external query engines and third-party tools, reducing catalog-specific integrations and connector maintenance.

Engine performance breakthroughs and view optimizations

The 482-e LTS release builds on core core execution engine updates to improve speed by 10% based on internal benchmarking, lower latency, and process complex queries transparently. This iteration further enhances the speed already associated with our query engine, delivering enhanced results for customers. 

Queries Exceeding RAM

To prevent Out of Memory (OOM) failures on massive queries, we are expanding support for our memory resilience execution mode backed by an object storage and/or a local disk tier in the embedded BufferService. This mode allows large queries to exceed available RAM while reducing  the runtime penalties of Fault-Tolerant Execution (FTE). This feature is in public preview.

PyStarburst Arrow Protocol 

The spooling protocol can now be configured to leverage Apache Arrow serialization alongside new PyStarburst methods. Now in public preview, this allows Python clients and data scientists to retrieve query outputs in a data-parallel format and pass Arrow chunks directly to Python data science tools without decoding, making result retrieval up to 7x faster.

Enhanced platform intelligence with AIDA

The 482-e release introduces crucial visibility, security, and context capabilities for the Starburst AIDA.

AIDA Studio, Skills, and Token Observability 

Now supported in 482-e, AIDA Studio provides a collapsible side panel offering configurable tools directly within chat sessions. Furthermore, AIDA Skills enters public preview, introducing granular access control so non-sysadmin users can author instructions and codify institutional knowledge. To manage costs, administrators gain a dedicated token consumption page in the Starburst Enterprise Admin navigation, providing visibility into usage trends across custom time ranges down to individual users.

External MCP Server OAuth Expansion 

Moving into public preview, AIDA’s external Model Context Protocol (MCP) server now supports expanded OAuth authentication standards, including OAuth Client ID/Secret and OAuth PKCE. AI platform teams can securely connect AIDA to a wider array of third-party enterprise systems to execute complex workflows grounded in enterprise context.

Data Product Enrichment Agent v2 

Now in public preview, the updated Data Product Enrichment Agent enables data SMEs to build AI-ready context in minutes. By combining user-provided scope descriptions and business rules with active data sampling—rather than relying strictly on raw metastore schema definitions—the agent automatically generates higher-quality metadata for data products.

Expanded open connector ecosystem

Starburst Enterprise 482-e expands federated access across unified lake formats, time-series systems, and SaaS endpoints.

• Great Lakes Connector (GA): A single unified connector spanning Hive, Iceberg, and Delta Lake table formats. Organizations can query across mixed table formats through one connector, cutting catalog sprawl and maintenance overhead.
• OpenAPI Connector (Public Preview): Query any OpenAPI-described REST system using standard SQL without waiting for custom connectors. Point the connector to an OpenAPI specification file to turn SaaS platforms like Jira, GitHub, and Datadog into queryable tables.
• kdb+ Connector (Public Preview): Capital markets and quant technology teams can now natively federate queries against kdb+ time-series data without sacrificing execution fidelity.
• OpenSearch Connector (GA): Upgraded to GA with multi-field pushdown and scrollable pagination support for large result sets, bringing production-grade federation to log analytics and SIEM workloads.

Critical breaking and configuration changes

This release includes several critical architectural changes and configuration updates that require attention prior to deployment. Review the full technical documentation to ensure cluster stability during the upgrade process.

Removal of Legacy Packaged HMS and Cloud Object Storage Support

• Hive Metastore Service Image Removed: The Starburst-packaged Hive Metastore Service (HMS) image and starburst-hive Helm chart have been completely removed after reaching end of support in 480-e. Organizations must migrate to Starburst Metastore before upgrading.
• Legacy Cloud Storage File Systems: Legacy Hadoop-based object storage support (io.trino.hdfs.s3.TrinoS3FileSystem and fs.hadoop.enabled=true for cloud storage) has been completely removed from the Delta Lake, Hive, and Iceberg connectors. Catalogs using legacy hive.s3.*, hive.azure.*, or hive.gcs.* configuration properties will fail to start. Migrate to fs.native-s3.enabled=true, fs.native-azure.enabled=true, or fs.native-gcs.enabled=true.

Connector Deprecations and Removals

• Snowflake JDBC Connector Removed: The snowflake_jdbc connector has been removed in favor of snowflake_parallel. Additionally, password-based authentication in the Snowflake connector is deprecated and will be removed in the November 2026 LTS release in favor of key-pair authentication.
• Alluxio Exchange & File System: Support for Alluxio-backed exchange storage for Fault-Tolerant Execution and the Alluxio file system across Delta, Hive, Hudi, and Iceberg connectors has been removed.
• Node-Level File System Caching: File system caching is no longer configured inside catalog properties (fs.cache.*). All cache configurations must be moved to node-level properties via cache-manager.config-files in config.properties.
• Starburst Data Catalog Property Renaming: Starburst Data Catalog has been renamed to Starburst Metastore. Properties prefixed with catalog.* (e.g., catalog.enabled) have been deprecated and renamed to metastore.* (e.g., metastore.enabled).

Implicit CHAR and VARCHAR Coercion Reversal 

The implicit coercion behavior between CHAR and VARCHAR types has been reversed. A CHAR value now coerces to VARCHAR with trailing spaces trimmed, and comparisons follow VARCHAR semantics without blank padding. To preserve legacy behavior until the November LTS release, administrators must explicitly set deprecated.legacy-varchar-to-char-coercion=true in their configuration.

Upgrade to Starburst Enterprise 482-e LTS Today

The 482-e LTS release marks a defining shift in how modern enterprises run, govern, and scale their data lakehouses. By embedding automated materialized view substitution, incremental Iceberg processing, and native Control Plane high availability, platform teams are equipped to run multi-cluster architectures with absolute performance and resilience.

To begin planning your deployment:

• View the full 482-e LTS release notes here.
• Review our AI and AIDA documentation here.
• Read our latest connector and migration guides here.