dbt Labs Introduces Fusion Engine for Enhanced AI-Ready Data Analytics

dbt Labs has launched the dbt Fusion engine, offering faster analytics delivery and reduced cloud costs, as announced in a press release. The new engine, built on Rust, enhances developer experience with features like SQL comprehension and state-aware orchestration.

dbt Labs has launched the dbt Fusion engine, offering faster analytics delivery and reduced cloud costs, as announced in a press release. The new engine, built on Rust, enhances developer experience with features like SQL comprehension and state-aware orchestration.

The Fusion engine powers the entire dbt platform, including the CLI, Orchestrator, Catalog, and Studio, providing a best-in-class developer experience. It introduces capabilities such as lightning-fast parse times, instant feedback loops, and live error detection, optimizing both developer efficiency and data platform costs.

Fusion's state-aware orchestration, available in beta, automatically runs jobs when sources are fresh and limits builds to changed models, helping organizations save on data platform compute. Early feedback indicates an average 10% cost savings, with further savings expected as Fusion matures.

The engine is now available for eligible dbt projects on Snowflake, with support for Databricks, BigQuery, and Redshift coming soon. dbt Labs also introduced a VS Code extension for local development and a source-available version of Fusion for the dbt community. dbt Labs continues to empower data teams to scale analytics in the age of AI.

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