dbt v2 lands: faster parsing, one shared adapter layer, and a docs experience that skips the giant manifest.json

dbt v2 introduces a unified architecture intended to merge the previously separate v1 and v2 codebases, reducing feature-delivery gaps and eventually consolidating the ecosystem around one engine and binary. To support migration, dbt v1.12 includes a v2 parser for compatibility testing and an autofix command for resolving deprecations, while v2 is generally available for most adapters. The release moves adapters into a shared binary layer based on the ADBC driver standard, allowing platforms such as Snowflake and Databricks to run together without dependency conflicts. Demonstrations showed significantly faster parsing on a large synthetic project, quicker SQL error detection in dbt’s full distribution, and a linter claimed to be substantially faster than alternatives. Docs v2 also replaces large manifest.json files with queryable Parquet files, enabling AI-assisted lineage and downstream-impact analysis, alongside a redesigned interface with DAG grouping views.

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