What the Fivetran-dbt Merger Means for the Data Ecosystem

For the last decade, large data platforms have increasingly moved toward full-stack integration. Snowflake now offers everything from pipelines to governance to AI agents within its platform. Databricks has expanded through acquisitions and native services to cover ingestion, observability, and machine learning on top of its lakehouse. Microsoft Fabric bundles ingestion, modeling, storage, and reporting into a single SaaS layer built on Azure. All three are aiming to control the entire data lifecycle within their environments.

Fivetran and dbt Labs have chosen a different path. Instead of building an all-in-one cloud ecosystem, the two companies are merging to combine their core capabilities. Fivetran handles data movement, helping teams pull information from dozens of sources into a central destination. dbt takes over from there, allowing analysts and engineers to transform that raw data into clean, reliable models.

The merger addresses a common gap in the data stack: managing ingestion and transformation across separate tools. While Fivetran and dbt have often been used together, they’ve remained independent systems — with different interfaces, metadata, logs, and monitoring.

Now, the combined company is positioned to deliver a more unified workflow — with shared metadata, consistent lineage, and coordinated testing from end to end. It also opens the door to features that weren’t practical before: integrated pipeline monitoring, transformation-aware scheduling, and stronger support for semantic modeling. For users, the impact is simple — fewer moving parts, and a more reliable foundation for analytics and AI.

(Credits: Fivetran)

“This is a refounding moment for Fivetran and the broader data ecosystem,” said George Fraser, CEO of Fivetran. “As AI reshapes every industry, organizations need a foundation they can trust — one that is open, interoperable, and built to scale with their ambitions. Our admiration for dbt and its remarkable community runs deep — this is about bringing together the best of both worlds to accelerate innovation and create lasting impact across the data community.”

There had been some quiet speculation that Fivetran and dbt Labs might eventually merge. After Fivetran acquired Census and Tobiko, some saw it as a sign the company was trying to expand beyond data movement into a transformation layer. Even dbt’s leadership acknowledged that the possibility had been on the table for a while.

“dbt has always stood for openness and practitioner choice,” said Tristan Handy, founder of dbt Labs. “For nearly a decade, I’ve worked to build data infrastructure that supports every engine, every format, every model, every tool, that acts as an abstraction layer across an entire ecosystem. By merging with Fivetran, we can accelerate that mission and deliver the open data infrastructure that practitioners and enterprises need in the AI era.”

While the merger itself isn’t a surprise, the question was always about timing. That moment came as expectations around data infrastructure shifted. Enterprise buyers now want tighter integration across ingestion, transformation, and governance. AI use cases have only added pressure, increasing the need for reliable, well-modeled data that is ready for production. Managing separate tools for each stage adds friction. In a market moving toward platform consolidation, staying independent was no longer sustainable.

The deal has cleared board approval on both sides, but it still needs to pass standard closing steps, including regulatory review. Once finalized, George Fraser will take the role of CEO of the new company, with dbt Labs founder Tristan Handy stepping in as president and co-founder.

(Ico Maker/Shutterstock)

The combined business is on track to reach nearly $600 million in annual recurring revenue (ARR). It already serves over 10,000 customers, including many of the world’s largest cloud data users. This scale positions them as a dominant force in enterprise data infrastructure.

Analysts see the merger as a smart move that pulls together two essential parts of the modern data stack. Kevin Petrie, an analyst at BARC U.S., said it makes sense on multiple levels. “Fivetran and dbt have worked closely for years. dbt adds the transformation layer that complements Fivetran’s strength in extraction and loading. Together, they’ve helped companies pull in data from many sources and get it ready for analytics in cloud environments.”

Sanjeev Mohan, founder of SanjMo, made a similar point. He noted that even though Fivetran had moved into reverse ETL with its Census acquisition, it still depended on dbt for modeling and transformation. “dbt is the 800-pound gorilla in the space,” he said. “Now Fivetran finally covers the full pipeline.”

Still, there are challenges ahead. Petrie warned that big mergers often come with internal friction. “Organizational disruption and turf wars are common,” he said. That could create a window for competitors to step in. Over time, though, he thinks the combined company could become the next Informatica — but only if it builds out stronger governance and observability features.

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