Apache Iceberg

Apache Iceberg on Snowflake got a lot simpler in 2026, and dbt's new catalog config is what makes it click

Apache Iceberg on Snowflake got much simpler in 2026, with dbt's new catalog config doing the key work of tying the setup together. Together with changes in Snowflake and DuckDB, it's now simple enough for a small team to get running in an afternoon.

What Open Data Infrastructure looks like with dbt Mesh

A new catalogs.yml v2 spec decouples dbt's Iceberg configuration from Snowflake-specific catalog integrations, and a live dbt Mesh demo showed three teams on Snowflake and Databricks sharing one set of Iceberg tables through Horizon and Unity catalogs via catalog federation, with no data copied. The session also introduced Managed Data Lake, which writes Iceberg or Delta metadata to a customer's own cloud storage using the open source Polaris catalog, and Lake Compute (private beta), which routes individual dbt models to DuckDB while the rest of the project stays on Snowflake.

How Obie Insurance cut its month-end close from 25 hours to 2 with dbt State and a lake house rebuild

Obie Insurance rebuilt its data platform on dbt and Apache Iceberg in a lake house architecture, cutting a critical month-end close process from over 25 hours to 2 hours. The post walks through how dbt State and the lake house rebuild made that reduction possible.

What makes a catalog open? Unity Catalog Advances the Open Lakehouse

Unity Catalog is the first catalog to support the Apache Iceberg REST catalog spec for REGISTER and UNREGISTER, enabling seamless table movement across catalogs without data duplication. By keeping managed tables in customer-owned storage, it provides full data portability while delivering advanced catalog features directly on tables you own.

Transactions are Generally Available, advancing warehousing on the Lakehouse

Multi-statement transactions are now generally available for Delta Lake and Apache Iceberg tables on Databricks, bringing native atomic guarantees to multi-table workflows. Backed by row-level concurrency and Unity Catalog governance, this capability allows practitioners to run critical warehouse workloads directly on open lakehouse data without maintaining separate warehouse systems.

UnityCatalog 0.7.0

Unity Catalog 0.7.0 enables native Apache Iceberg REST catalog support by default, allowing external query engines to read, write, and manage Iceberg tables directly. Dropping managed tables, volumes, or models now automatically and permanently purges underlying cloud storage files after a default seven-day delay.

Announcing Workday Data Connect federation in Unity Catalog

The new Workday Data Connect connector (Beta) brings zero-copy federation to Unity Catalog, allowing teams to query Workday's shared Iceberg tables directly from cloud storage without ingestion pipelines or data duplication. Queries run on Databricks compute under Unity Catalog governance, enabling you to combine live HR and financial data with existing Databricks datasets for Genie-powered exploration, workforce analytics, and AI.

Delta Lake 4.4.1

Delta Lake 4.4.1 adds safeguards for catalog-managed tables by blocking unsupported cleanups and skipping automatic maintenance so writes can succeed reliably. It also fixes snapshot construction errors caused by unratified staged commits, allowing safe re-enablement of S3A fast listing.

Read Restrictions and Catalog Labels: Unifying governance across engines and catalogs

Apache Iceberg has introduced read restrictions and catalog labels, two new specifications designed to standardize policy enforcement across different engines and catalogs. These additions eliminate fragmented enforcement by delegating access decisions to trusted engines and making governance metadata portable across federated catalogs.

Unifying governance across engines and catalogs in the Open Lakehouse

Apache Iceberg now has two new specs, read restrictions and catalog labels, that standardize policy enforcement across engines and catalogs by letting trusted engines handle access decisions directly and making governance metadata portable across federated catalogs. Together with centralized enforcement for untrusted engines, they give the Open Lakehouse a clear governance model covering every access pattern.

Open Table Formats Explained: Iceberg vs. Delta vs. Hudi

Delta Lake and Apache Iceberg now share governance through catalog-coordinated commits, while metadata trees and transaction logs enable data skipping and time travel that cut query costs without sacrificing access to prior table versions. Interoperability features like Delta Lake UniForm and Unity Catalog let teams query the same underlying data natively as either format across engines like Spark and Trino, reducing vendor lock-in.

UnityCatalog 0.6.0

This release adds Apache Spark 4.2 support and introduces metric views and SQL views as governed catalog objects for semantic layers and query management. UC access tokens now expire after 24 hours by default, requiring periodic re-exchange instead of the previous indefinite validity.

Delta Lake 4.4.0

Delta Lake 4.4.0 supports Apache Spark 4.2 and adds identity columns and generated-column support in SQL DDL. The release expands UC Delta API integration to Delta Kernel and the experimental Flink connector for catalog-managed tables, introduces Flink upsert mode with merge-on-read updates, and improves VOID-column and partition handling.

Delta Lake 3.3.3

Delta 3.3.3 fixes transaction log retention bugs that broke time travel and CDF reads, and a Delta Sharing deletion vector cache bug causing long-running queries to fail. It adds opt-in RANDOMIZE_FILE_PREFIXES to spread S3 object keys for high-throughput workloads and upgrades Delta Sharing client for improved OAuth and retry handling.

dbt Summit 2026: the keynotes and product sessions

dbt Summit 2026 previews major platform evolutions, including a Rust-based dbt Core rebuild with Arrow adapters, Parquet-backed artifacts, and dbt State to eliminate redundant model runs and reduce compute spend by 30%. The upcoming sessions also focus on open lakehouse architectures with Apache Iceberg, portable semantic standards via Apache Ossie, and governed agentic workflows using dbt Wizard.

Delta Lake 4.3.1

Delta Lake 4.3.1 fixes OAuth authentication failures in the Delta REST Catalog caused by incorrect key lowercasing and enables S3A fast listing when using OSS UnityCatalog's CredScopedFileSystem wrapper. It also prevents the reserved is_managed_location property from persisting into managed table metadata.

Delta Lake 4.3.0

Delta 4.3.0 deepens Unity Catalog integration by making it the source of truth for managed table operations via the UC Delta REST API, introduces replaceOn/replaceUsing DataFrame APIs for selective row-level data replacement, and improves UniForm with atomic Iceberg conversion and incremental metadata updates. Delta Sharing gains streaming support, Change Data Feed capabilities, and Trigger.AvailableNow, plus performance improvements like better V2 checkpoint parallelization and variant column statistics for data skipping.

Introducing OpenSharing: the Next Evolution of Delta Sharing for the Agentic Era

Databricks has introduced OpenSharing, a Linux Foundation-hosted evolution of Delta Sharing that expands zero-copy sharing beyond tabular data to models, agents, and semantic context across Delta Lake, Apache Iceberg, and Parquet. The enterprise implementation on Databricks enables governed sharing of Genie Agents via Unity Catalog, automated private networking with SecureConnect, and low-latency multi-cloud access via Global Distribution.

Advancing Apache Iceberg on Databricks: Iceberg v3 GA, Open Sharing, and Unified Governance

Unity Catalog now offers GA support for Managed Iceberg, Iceberg v3, and Foreign Iceberg, making it the most comprehensive and production-ready Apache Iceberg catalog with open APIs, catalog federation, and secure sharing. Future versions of Iceberg and Delta will converge on a unified metadata structure, eliminating the tradeoff between interoperability and performance.

Interoperability Between Unity Catalog and Google BigQuery via Catalog Federation

Google Cloud now supports catalog federation to Unity Catalog, enabling BigQuery users to read tables in Unity Catalog without duplication. Unity Catalog also supports catalog federation to Google Cloud's Lakehouse, allowing it to read Iceberg tables written from BigQuery and other engines.

Delta Lake 4.2.0

Delta 4.2.0 enables atomic REPLACE TABLE, RTAS, and DPO for catalog-managed tables, enhances streaming capabilities, and adds a Kernel-based Flink connector. The release makes Variant generally available, adds geospatial and collation support, and includes comprehensive security hardening.

Delta Lake 4.1.0

Delta Lake 4.1.0 supports Apache Spark 4.1.0 and introduces conflict-free enablement of Deletion Vectors and Column Mapping on existing tables without blocking concurrent writes. The release requires Java 17 and Spark 4.0.1 or higher (dropping Spark 3.5), adds full catalog-managed table support in Delta Kernel for Unity Catalog integration, and fixes MERGE/INSERT struct expansion bugs.

Delta Lake 3.3.0

Delta Lake 3.3.0 adds Identity Columns for automatic unique keys, VACUUM LITE for faster transaction log-based cleanup, and enables Row Tracking backfill on existing tables for row-level lineage tracking. UniForm Iceberg can now be enabled on existing Delta tables without data rewriting, and Type Widening is now supported in Delta Kernel for reading type-evolved tables.