dbt Blog

A founding member reflects on the first six months of the dbt Champions program, covering 30 Champions and 20 Big Projects including Zoe Yim's Pipeline to Plate, Adedamola Onabanjo's Messy MRR, and the open-source Agent Trust for dbt.

dbt State now has a free plan after the trial period ends, with a monthly 1,000 DATT allowance that resets on the 1st and requires no card or contract. dbt platform users get a 2,000 DATT monthly allowance through March 2027.

A new datasharing: true profile credential switches the dbt-redshift adapter's metadata queries to Redshift-native SVV_* system views and SHOW APIs, making cross-database writes succeed and unlocking dbt Mesh cross-project refs, Advanced CI, and workload isolation for Redshift data sharing. The same migration away from legacy Postgres pg_* catalog views speeds up metadata resolution under high concurrency. The flag is currently in Beta on the Latest release track and not available on Compatible or Extended tracks.

dbt State is generally available, comparing each node's compiled SQL and upstream freshness to reuse, clone, or rebuild models at the node level, with pricing at $0.094 per daily active target table and each test counted separately. Views using select *, non-deterministic Jinja, and BigQuery external sources without loaded_at_field or loaded_at_query are always rebuilt; former state-aware orchestration users must map build_after to lag_tolerance and require_fresh_data_from, defaulting to 45m and any when build_after is absent.

dbt v2, a full Rust rewrite of the dbt engine that parses a 10,000-model project up to 10x faster than v1, and dbt State, which checks warehouse metadata and model SQL to build, skip, clone or defer each run, are both generally available. Also announced: Fivetran Context Layer (Private Beta) with the open source Agents Schema standard, dbt Charts (Public Beta) for governed BI as version-controlled YAML, dbt Wizard for the dbt platform (Public Preview) plus Wizard CLI (Public Beta) and Wizard Desktop (Private Beta), Lake Compute (Private Beta) on DuckDB against Apache Iceberg tables, and an open lakehouse vision for customer-owned storage and compute.

dbt State is generally available and reads model SQL plus warehouse metadata each run to decide whether to build, skip, clone, or defer a node, without selection syntax or manifest scripts. Pricing is consumption-based on daily active target tables, with every reuse after the first in a day free and a 30-day trial. It supports Snowflake dbt Projects, includes Cost Insights, a richer dbt state explain experience, and concurrent build management.

dbt Core v1.12 is now generally available. See the blog post for new features and upgrade guidance.

The dbt Snowflake Native App will be retired in November 2026.

dbt Core v2.0 moves the open-source project to the Rust-based Fusion engine under an Apache 2.0 license, delivering dramatic CLI speed improvements and Parquet artifact files for local DuckDB queries. Fusion continues as a superset with SQL comprehension features.

The Open Semantic Interchange (OSI) project has been accepted into the Apache Incubator and renamed to Apache Ossie (Incubating). The specification, community, and mission remain unchanged; all references to OSI are historical and will be removed over time.

We've seen this pattern often enough to name it. A team migrates to dbt, spends six months, and ends up with a dbt project that looks exactly like their old workflow, just with Jinja templating instead of drag-and-drop. The data model still has the same problems. It's only…

What's missing from every agentic data pipeline diagram

What is context engineering?

The AI readiness gap is bigger than it looks

AI agents do not fail because of a weak model. Rather, they fail because of using infrastructure that was never meant for autonomous decision-making.

When it comes to getting their data AI-ready, many organizations start with cleaning and structuring their data and then simply stop. This is an important first step, but it's not the last step, because AI-ready data relies heavily on context: the layer of meaning that explains…

It's been a big few months of shipping at dbt. We've got a lot to cover — from the dbt Developer Agent going into preview, to making the upgrade to the dbt Fusion engine self-serve, to new ways to lock down your account security, to quality-of-life improvements for practitioners…

Coding agents are doing a tremendous amount of useful work today. Since Claude Code dropped last year, followed by Opus 4.5 and GPT 5.2, software engineering has very clearly passed a phase change. We've gone from copilot-style autocomplete to agents that can run end-to-end…

dbt Developer Agent is now available in Preview—grounded in your dbt project so you ship faster without breaking downstream.