Is the Fivetran–dbt Labs merger the beginning of the end for fragmented data stacks?

In a move that could mark the beginning of the end for fragmented data stacks, Fivetran, a global leader in automated data movement, has entered into a definitive all-stock agreement to merge with dbt Labs, the transformation platform that helped define the modern data stack. Announced on October 13, 2025, the merger will create a unified open data infrastructure company with nearly USD 600 million in annual recurring revenue (ARR) and a customer base spanning more than 10,000 organizations worldwide.

George Fraser, co-founder and CEO of Fivetran, will serve as CEO of the new entity, while dbt Labs founder Tristan Handy will assume the role of President and Co-Founder, focusing on open source strategy and community engagement. Both firms are pledging to preserve their current product lines, with dbt Core remaining open source and fully supported. The transaction has received board and shareholder approval on both sides and is currently pending regulatory clearance. Until then, Fivetran and dbt Labs will continue to operate independently.

This merger is not just about market share—it is a strategic play to define the next chapter of enterprise data architecture by creating what both companies call “open data infrastructure.”

Why this merger matters for enterprise AI strategies and open-source data transformation

The rationale behind the Fivetran–dbt Labs merger is deeply tied to the evolving demands of AI-driven enterprises. As organizations across industries scale artificial intelligence projects, there is a growing need for reliable, explainable, and interoperable data infrastructure. The unification of Fivetran’s automated data ingestion capabilities and dbt’s declarative transformation framework offers an end-to-end pipeline that is purpose-built for AI workloads.

Fivetran has been widely adopted for its low-latency, high-reliability pipelines that extract and load data from thousands of sources into data warehouses and lakes. Meanwhile, dbt Labs has cultivated one of the largest communities of data practitioners around its structured, SQL-based transformation logic, used to convert raw data into analytics-ready datasets.

According to George Fraser, the driving force behind this move is the need for a scalable foundation that supports openness and automation without locking customers into specific compute engines or vendor ecosystems. The merged entity aims to simplify complex data workflows, making it easier for enterprises to build AI and analytics use cases without stitching together multiple incompatible tools.

How long-standing synergies between Fivetran and dbt Labs led to this strategic merger

The merger may appear sudden, but the relationship between Fivetran and dbt Labs spans more than a decade. Tristan Handy, who launched dbt as Fishtown Analytics in 2016, recalled how the two companies were early collaborators. During the formative years of the “modern data stack,” both platforms were frequently deployed together in implementations combining Amazon Redshift, Looker, and Mode Analytics.

Handy noted that the merger had been an ongoing discussion topic for several years, especially among stakeholders and mutual investors. One board member reportedly described the merger as “an obvious win” and encouraged both leaders to align when the time was right. That time, according to Handy, arrived when both firms reached operational maturity, with predictable ARR, active communities, and robust product pipelines.

The deal signals a culmination of parallel journeys—both companies grew out of similar industry pain points and built solutions that became indispensable for cloud-native data teams. Rather than remaining separate but complementary entities, the companies are now consolidating to build something more integrated, while retaining the open and modular philosophy that brought them success.

What does open data infrastructure mean, and how does it evolve the modern data stack?

Fivetran and dbt Labs are positioning their new platform as “open data infrastructure,” a term that extends beyond the widely used but fragmented concept of the modern data stack. While the modern data stack describes a composable architecture of best-in-class tools, open data infrastructure implies a tighter integration across ingestion, transformation, metadata, and activation layers—without sacrificing flexibility or interoperability.

This unified architecture is built on open standards such as SQL and Apache Iceberg. It is designed to work with any compute engine, business intelligence tool, or AI model, thus enabling organizations to scale data workloads without being boxed into closed ecosystems.

Tristan Handy emphasized that this model removes the duct tape many data teams have used to hold together disparate tools. Instead, open data infrastructure offers a more elegant and predictable foundation that abstracts complexity, accelerates time to insight, and supports enterprise-grade performance across cloud platforms.

What will remain unchanged for users and open source contributors of Fivetran and dbt?

Both Fivetran and dbt Labs have explicitly committed to maintaining the current developer experience and community support for their platforms. dbt Core, the open-source engine that enables SQL-based transformations, will continue under its existing license. dbt Fusion, its commercial offering, will also continue without disruption.

Fivetran, which has historically leaned toward proprietary development, has already made substantial contributions to dbt’s open-source ecosystem. The company has authored over 100 open-source packages that are widely used by data teams globally and maintains a full-time staff dedicated to open-source efforts. With the merger, there are plans to explore how more of Fivetran’s internal tooling—such as connectors—could be released under permissive licenses to further support community-led innovation.

Tristan Handy will retain oversight of all community and open-source strategy and will serve on the board of the unified company. This structure is intended to reassure dbt’s user base that the open-source ethos will not be diluted by commercial integration.

How will the unified company simplify data engineering and reduce operational complexity?

Both companies have historically focused on reducing toil in the data engineering process. Fivetran’s “set-it-and-forget-it” ingestion pipelines and dbt’s declarative transformation language were designed with simplicity in mind, allowing data practitioners to focus on business logic rather than backend maintenance.

Together, the platforms eliminate redundant scripting, orchestrate workflows seamlessly, and ensure traceability across the entire data lifecycle. George Fraser likened the goal to flipping a switch and instantly getting clean, trusted data—akin to electricity. Handy compared the user experience to Apple’s ecosystem, where everything works together out of the box without friction.

This new end-to-end solution is aimed at IT leaders, engineers, and analysts who are seeking to deploy high-quality analytics and AI with fewer manual interventions and lower total cost of ownership.

What do analysts and institutional investors see in the Fivetran–dbt Labs combination?

Early sentiment from institutional observers has been favorable. Analysts view the merger as a natural consolidation play in a maturing market. The combination of ARR scale, complementary product lines, and shared community goodwill makes the new entity well-positioned to compete against vertically integrated players like Snowflake and Databricks.

There are also implications for how this merger might influence enterprise procurement decisions. With so many large organizations already relying on both Fivetran and dbt, the merged platform could become the default infrastructure for structured data pipelines across industries, from finance and pharma to e-commerce and telecom.

Investors also see promise in the open data infrastructure positioning, which could help the company differentiate itself in a crowded landscape increasingly dominated by cloud hyperscalers offering bundled tools. The firm’s vendor-agnostic approach may resonate with CIOs and data leaders who value flexibility and future-proofing in long-term digital transformation strategies.

Which financial and legal advisors are guiding the Fivetran–dbt Labs merger and how is governance being structured for the new open data entity?

The merger has been structured as an all-stock transaction. Financial and legal advisory services were provided by a group of top-tier firms. Qatalyst Partners acted as the exclusive financial advisor to Fivetran, while Deloitte & Touche LLP provided due diligence support. Legal advisory came from Wilson Sonsini Goodrich & Rosati and DLA Piper LLP.

On dbt Labs’ side, Morgan Stanley served as the exclusive financial advisor, and Latham & Watkins LLP acted as legal counsel. The merger is pending customary closing conditions, including regulatory approval.

Both companies have confirmed that governance frameworks are being designed to preserve operational independence where necessary, while aligning on strategic objectives such as open source stewardship and enterprise go-to-market execution.