Article

Introducing Capacity-Based Pricing

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February 11, 2025

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5 min read

Summarize this article with:

At Airbyte, as we've developed our Teams and Enterprise offerings, we've worked closely with our largest customers to better understand their evolving data needs. In conversations with 500+ companies, we've seen firsthand that traditional row-based pricing just doesn't work for at-scale teams, especially as data organizations face a rapidly changing landscape driven by LLMs, data lakes & data modernization.

Volume based pricing is unpredictable, fluctuates month to month, and ultimately penalizes companies adapting to shifting data demands. The real value of fresh, accessible data isn’t tied to volume—it’s defined by how that data is used once it reaches your systems.

Charging by the row created challenges for our larger customers:

Even with governance controls, a sudden spike in upstream data volume could drive up costs—without a meaningful change in the value of the data being moved.
A database pushing terabytes of low-priority compliance logs could overshadow the cost of 20+ high-value source connectors, despite their greater overall impact.
It hinders your ability to quickly innovate by conducting experiments with new datasets.

That said, pay-as-you-go and row-based pricing can also work well for certain customers—especially smaller organizations with fewer data sources and more predictable data needs, looking to avoid building custom ETL solutions in-house.

Our New Approach: Capacity-Based Pricing

We’re introducing capacity-based pricing to our Teams and Enterprise products to address these challenges head on. Capacity-based pricing scales based on your actual infrastructure needs, rather than the amount of data you move. Instead of charging by data volume, we price based on Data Workers, which measure the horsepower required to run data pipelines efficiently. This makes for predictable and scalable pricing, as customers pay for processing capacity and not for fluctuating data usage.

We have been rolling out this new pricing structure over the past few months with selected Teams and Enterprise customers. Each customer starts with a base package that includes an initial number of Data Workers (processing units that handle data movement). If your data needs evolve, you can easily add more Data Workers to support new workloads.

In this new model, there are only two primary factors to consider to estimate your usage:

The number of Airbyte connections you need (number of data sources)
The frequency at which you need your data refreshed (hourly, daily, real-time)

This makes for streamlined and straightforward pricing conversations that don’t require complex forecasting and scenario planning, and ultimately will lead to a better experience with Airbyte as teams aren’t worried about the amount of data they move.

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An Update on our Enterprise Products

If it’s been a while since you last evaluated Airbyte as a possible data movement solution, I’m happy to share that we’ve been hard at work, recently introducing:

Airbyte Teams, a fully-managed product for larger data teams requiring governance controls while looking to simplify pipeline operations.
Airbyte Self-Managed Enterprise, a data movement platform that runs entirely on your own infrastructure, ensuring no data ever leaves your environment.‍
Airbyte 1.0 – our biggest launch ever, including faster speeds, and a Connector Builder for extracting data from any SaaS API.

At Airbyte, pricing is designed to empower you, not limit you. Our capacity-based model ensures transparency, fairness, and flexibility—scaling seamlessly with your business as your data needs grow.

On a personal note, when John and I started Airbyte, our goal was to make data accessible and empower teams to drive innovation. That required not just great technology but also a pricing model that could scale with the exponential growth of data.

Volume-based pricing was always a major blocker, which is why so many teams turned to Airbyte Open-Source early on. We even experimented with CPU-based pricing but lacked the market insight to make it work at the time.

Today, I’m incredibly proud to introduce a new model that removes these barriers and truly unlocks data for everyone, everywhere.

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