FiveTran and dbt Labs merger: A new giant in the modern data stack

The data world is abuzz with the news of FiveTran and dbt Labs merging, a move that creates a powerhouse with $600M in combined revenue and over 10,000 customers. To put things in perspective, Snowflake, the modern data warehouse leader, has around 12,000 customers and about $3.6B in revenue. Databricks is of similar scale. That means the combined FiveTran–dbt entity is now within striking distance—perhaps not in immediate revenue (more on that later), but definitely in ecosystem influence.

Why this merger matters

This merger brings together the core building blocks of the modern data stack under one umbrella:

• FiveTran for automated data ingestion (ETL/ELT)
• dbt for transformation-as-code
• Census (which FiveTran acquired earlier) for reverse ETL

Together, they cover nearly the entire data lifecycle, from source to warehouse to activation. For customers, this means fewer vendor contracts, simplified integration, and potentially a single pane of glass to manage their data workflows.

This is a natural precursor to having end-to-end data infrastructure that is set up and managed by AI.

With dbt’s code-driven transformation and FiveTran’s managed pipelines, the stack becomes highly declarative and configurable. The next logical step—and one we’ve been pursuing at RudderStack with data collection (via EventStream), transformation (via Profiles), and activation (via ReverseETL) all managed as code—is AI-native data infrastructure.

A push toward open standards

FiveTran has been increasingly vocal about supporting open data standards like Apache Iceberg.Now, with dbt’s transformation layer and orchestration control, the company gains a strong influence over where computation happens.

Imagine a near-future scenario:

• A customer runs FiveTran + dbt jobs on Snowflake today.
• Tomorrow, they could seamlessly shift computation to Iceberg-based storage, while keeping results queryable in Snowflake (via its Iceberg support).

That could mean massive savings on Snowflake compute bills—not great news for Snowflake, but a huge win for customers and for FiveTran’s platform control.

This move signals the next battleground in the data ecosystem:

Control over compute and cost efficiency, not just data movement.

The not-so-exciting side

Of course, it’s not all upside. Fivetran’s usage-based MAR pricing is often described as premium—and for high-volume updates or backfills it can escalate quickly, with reviewers warning it can “blow up a budget.” By contrast, dbt grew from open-source roots and cultivated an active community (now 100,000+ members) earning a reputation as the friendlier, community-driven player.

That culture clash is already raising concerns. Many on social media and Hacker News worry that dbt’s open model might suffer under FiveTran’s commercial focus, especially as the combined company eyes an IPO.

To dbt’s credit, they’ve publicly reaffirmed their commitment to open source—at least for the foreseeable future. But how that balance holds once Wall Street’s growth expectations kick in remains to be seen.

What this means for the customer data industry

This merger effectively reshapes the center of gravity in the modern data stack:

• It may challenge Snowflake’s dominance by giving customers credible, cost-efficient alternatives.
• It puts dbt’s developer community at the heart of an enterprise data platform.
• And it accelerates the trend toward consolidation and AI-native data management

Final takeaways for the customer data space

The FiveTran–dbt merger isn’t just a business deal. It’s a signal of where the data ecosystem is heading: toward unified, intelligent, open, and eventually AI-managed infrastructure.

Exciting days lie ahead for everyone in the modern data space.