Data News — dbt Coalesce 2025

2025-10-19 · Source: blef.fr - Blog · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Software Development & Engineering · Depth: Advanced, medium

Summary

The article discusses the dbt Coalesce 2025 conference and the recent merger between dbt Labs and Fivetran, analyzing its implications for the data ecosystem. The author, a long-time dbt Core advocate, reflects on the evolution of data tooling from the Big Data era to the Modern Data Stack and the current Analytics and AI Stack. The merger aims to create a "first-of-its-kind open data infrastructure," with dbt Labs emphasizing open standards over strictly open-source contributions. Key announcements include dbt Fusion for cost cutting and improved developer experience, support for Iceberg and data lakes via Fivetran, and the Open Semantic Interchange (OSI) initiative. The author expresses disappointment with Coalesce 2025's talk quality and a perceived shift in dbt Labs' focus towards enterprise clients, moving away from its community-driven, open-source roots.

Key takeaway

For data engineers and architects evaluating their data transformation stack, the dbt Labs and Fivetran merger signals a strategic pivot towards enterprise solutions and open standards, potentially at the expense of pure open-source commitment. You should assess whether the new offerings, like dbt Fusion and expanded data lake capabilities, align with your team's technical philosophy and budget, especially if your current operations rely heavily on dbt Core's community-driven model. Be prepared to explore alternative open-source transformation tools if the new direction does not meet your needs.

Key insights

The dbt Labs-Fivetran merger signals a shift towards enterprise-focused, open-standard data infrastructure, potentially alienating open-source advocates.

Principles

• Open standards do not always equate to open-source.
• Consolidation in data tooling is driven by AI's demand for speed.
• Community-driven tools can evolve into enterprise solutions.

Method

The merged dbt Labs and Fivetran aim to provide an open data infrastructure by focusing on open standards, supporting Iceberg catalogs, and developing tools like dbt Fusion for cost-efficient data transformation.

In practice

• Evaluate dbt Fusion for potential 50% cost savings.
• Consider alternatives like SQLMesh, Bauplan, Bruin, Lea, or dltHub.
• Explore Open Semantic Interchange (OSI) for metric definition.

Topics

• dbt Fivetran Merger
• Open Data Standards
• dbt Fusion
• Modern Data Stack
• Data Transformation

Code references

• dbt-labs/dbt-mcp
• Bl3f/yato
• carbonfact/lea

Best for: Investor, CTO, VP of Engineering/Data, Data Engineer, MLOps Engineer, AI Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by blef.fr - Blog.