Everything we announced at dbt Summit and why it matters

At dbt Summit 2026, dbt Labs and Fivetran presented a product strategy centered on the idea that the governed data foundations used for trustworthy analytics are also essential for reliable AI. Key releases include dbt v2, now generally available as a unified Rust-based engine with improved SQL comprehension and performance, and dbt State, which selectively rebuilds changed models to reduce compute use and simplify freshness management. The companies also introduced Lake Compute in private beta, allowing individual dbt models to run against Apache Iceberg tables through a DuckDB-based engine while others remain on a warehouse. To support AI applications, dbt expanded integrations for its Semantic Layer, MCP Server, and Agents Schema, while Fivetran announced its Context Layer for converting structured and unstructured business information into maintained AI context. dbt Wizard, available across the platform, CLI, and desktop environments at varying preview stages, provides a project-aware agent for analytics engineering and conversational exploration, while dbt Charts in public beta aims to bring dashboards into version-controlled, YAML-based development workflows alongside data models.

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