As organizations explore new data-intensive business opportunities such as AI, many are forced to rethink their data stacks, which often struggle to support modern data workloads. As the demands imposed on data teams grow, data professionals must carefully evaluate how they can use data integration tooling and finite engineering resources to drive impact.

This is where total cost of ownership, or TCO, matters. TCO provides a comprehensive view of what it takes to move, manage, and maintain data over time, which is critical for analytics and AI initiatives that depend on reliable, continuously available data.

Fivetran delivers business value beyond surface-level pricing, and our customers consistently translate that value into measurable return on investment. The question is where to start quantifying that impact. The Fivetran TCO calculator provides a practical way to do that by estimating engineering effort, maintenance, and downtime in one place. This makes it easier for you to assess the tradeoffs and understand the broader operational impact of changing from DIY pipelines to a managed service like Fivetran.

Introducing the Fivetran TCO calculator

Understanding the true cost of data integration is not always straightforward. Every organization has different team structures, data sources, reliability needs, and levels of complexity. Many of the most expensive factors never appear as line items in a budget.

That is why we built the Fivetran TCO calculator.

The calculator is a simple, self-serve tool that estimates what teams are currently spending to build and maintain data pipelines and compares that to Fivetran’s fully managed approach. It accounts for engineering time, ongoing maintenance, downtime, and other operational effort to provide a clear, systematic view of long-term ownership costs.

How to use the Fivetran TCO calculator

The Fivetran TCO calculator is designed to be fast and easy to use, giving you directional insights without requiring deep data or detailed models to get started.

Step 1: Select your company size

Start by selecting your company size. This sets baseline assumptions about team structure, number of data sources, and pipeline complexity based on organizations of similar scale.

Step 2: Review and adjust key TCO inputs

Next, review the pre-filled inputs on the left that represent the primary contributors to data integration costs. These values are automatically populated based on your selected company size and common patterns we see across data teams, informed by industry benchmarks from Fivetran’s data integration benchmark report (2026).

Each of these values can be adjusted to reflect your current data integration setup. If the numbers do not reflect your current setup, you can update them to match how your team operates today. Each field includes an in-line description and a tooltip to explain what the input represents and how it is used in the calculation.

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‍Step 3: Review your results

Once the inputs are complete, the calculator shows two primary outputs:

• Your estimated cost of manually building and maintaining data pipelines today
• Estimated savings in time and dollars with a fully managed platform like Fivetran

The goal is not exact precision. The goal is visibility into where hidden effort, risk, and cost accumulate over time.

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Why we pre-filled the values we did

Every input in the Fivetran TCO calculator is fully editable. We pre-filled the values to make the calculator easier to use and to highlight the cost drivers that teams often underestimate. The pre-filled numbers are meant to guide your estimate and help surface hidden effort that may not show up clearly in budgets or planning models.

Downtime cost

Data downtime is one of the most underestimated contributors to total cost of ownership. Even short disruptions can delay reporting, stall analytics and AI workflows, and slow decision-making across the business.

Fivetran’s data integration benchmark report (2026) found that enterprise data teams report an average downtime impact of approximately $50,000 per hour, driven by lost productivity, stalled operations, and the engineering effort required to diagnose and recover from pipeline failures. Defaults for smaller companies are scaled down to reflect fewer downstream dependencies and lower operational exposure.

Downtime hours per week

Pipeline downtime is not limited to full outages. It also includes delayed syncs, failed jobs, and the time teams spend waiting for manual fixes before data is usable.

Research found that enterprise teams average approximately 60 hours of pipeline downtime per month, driven by pipeline failures, delayed recoveries, and time spent restoring data availability. This equals roughly 15 hours per week for large organizations.

Defaults for smaller companies assume less frequent disruption due to fewer pipelines and lower complexity, while still accounting for the time spent diagnosing and resolving issues. 

Time to build pipelines

Data teams often underestimate the complexity and upfront effort involved in building data pipelines. Initial development, testing, validation, and rework all contribute to longer time-to-value.

The calculator’s default build-time estimates are based on industry benchmarks and community data, which commonly cite 2–3 weeks (80–120 hours) to build and test a stable data pipeline from scratch, depending on source complexity and internal expertise. Smaller organizations tend to integrate fewer, more standardized systems, while mid-sized and enterprise teams often work with a mix of APIs, internal tools, and legacy systems that increase build time per connection.

Start calculating your total cost of ownership

The upfront price of a data integration tool is only part of the story. In the long run, engineering effort related to maintenance and downtime often account for the majority of what organizations spend to keep data reliable and accessible.

The Fivetran TCO calculator gives you a practical way to estimate and understand what your current approach really costs and where a fully managed platform can reduce operational burden and long-term ownership costs.

Use the calculator to review the assumptions, adjust them to reflect how your team operates today, and see how changes in scale or complexity affect total cost over time.

To explore further, visit our TCO landing page. 

If you want a deeper, more tailored view, our team can help you build a custom estimate based on your data strategy, existing tools, and business priorities. 

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