Fivetran Pricing in 2025: How Much Will It Cost?

Fivetran has long been a key player in the data integration space, offering automated pipelines to sync data from hundreds of sources into cloud data warehouses. However, as of March 2025, Fivetran is rolling out significant changes to its pricing model, shifting how businesses are charged for data usage.

The most notable change is that Monthly Active Rows (or MAR) will now be calculated per connection rather than across an entire account. This means that businesses using multiple connectors will now see each integration billed separately. While some customers may benefit from this shift, others could see increased costs depending on the number of active connections and data volume.

For companies relying on frequent data syncs, particularly in marketing, e-commerce, and financial reporting, it’s crucial to understand how these pricing changes could impact budgeting. This article breaks down the current Fivetran pricing structure, the confirmed changes coming in March, and how it compares to alternatives like Weld.

How Fivetran’s pricing model works

Fivetran operates on a usage-based pricing model where costs are based on MAR — the number of rows inserted, updated, or deleted in a connected database within a given month.

Key details of Fivetran’s pricing model:

• Monthly Active Rows: Any data change (new rows, updates, or deletions) contributes to your MAR count.
• Connection-level pricing (from March 2025): Instead of calculating MAR across an entire account, each connection will now be billed separately.
• Transformation charges: Fivetran charges for successful data model runs, with free tiers up to 5,000 runs per month.
• Re-synced identical rows: These no longer count toward MAR usage, helping some businesses optimize costs.

Previously, companies managing multiple data sources under one account could distribute their MAR across connections, optimizing costs. However, the new pricing model applies MAR per connection, meaning that companies with several integrations may see a significant increase in costs. Fivetran provides a pricing estimator that allows users to model their monthly expenses based on MAR usage. Additionally, their official documentation explains the pricing model in detail.

What is Monthly Active Rows?

MAR is Fivetran’s method of measuring data volume, ensuring that businesses only pay for data that changes.

💡 Here’s how MAR works:

• A row is counted as active if it is inserted, updated, or deleted.
• Multiple updates to the same row in a month still count as 1 MAR.
• Deleted rows count as MAR because Fivetran registers them as a change.
• MAR resets every month, meaning a previously updated row will be counted again if modified the next month.

Previously, businesses could spread their MAR usage across multiple connections within one Fivetran account, keeping costs manageable.

However, as of March 2025, MAR is now calculated per connection, meaning each data source has its own MAR count and pricing.

This change significantly impacts costs for companies syncing multiple high-volume data sources.

Fivetran pricing plans

Fivetran offers four pricing tiers, with the cost per million MAR varying across each plan. Each tier includes different features, such as sync frequency and security options, tailored to businesses of different sizes and data needs.

A key update in March 2025 is the shift to connection-based MAR billing, which could lead to higher costs for businesses using multiple connectors. Additionally, annual contracts require a minimum commitment of $12,000, which may not be ideal for smaller teams or companies with fluctuating data needs.

What to consider when budgeting for Fivetran

For companies evaluating Fivetran, it’s crucial to assess data volume fluctuations and the number of connectors in use. Seasonal spikes, marketing campaigns, and product catalog updates can significantly impact MAR usage, potentially leading to unexpected cost increases.

Fivetran does offer some cost-saving measures, such as a 5% discount on annual contracts and a Startup Program providing $50,000 in free services for eligible early - stage companies. However, organizations seeking more predictable pricing should consider alternative ETL solutions that offer fixed-cost models.

Fivetran vs. Weld: A pricing comparison

For businesses weighing Fivetran against other ETL solutions, it’s worth comparing its pricing model to alternatives like Weld, which takes a fixed-tiered approach rather than usage-based billing.

Which pricing model is better?

Fivetran’s MAR-based pricing can work well for businesses with low data volume but high-value insights, allowing them to pay only for the rows they use. However, for companies managing multiple connections or frequently updating large datasets, the new per-connection billing structure could lead to unpredictable costs.

Weld’s fixed-pricing approach is designed for teams that want to avoid row-based billing fluctuations and maintain cost predictability. Businesses integrating multiple data sources — especially those in marketing, sales, and e-commerce — may find Weld’s flat-rate model more budget-friendly compared to Fivetran’s per-connection MAR pricing.

Final thoughts

With its upcoming pricing changes, Fivetran remains a powerful choice for data integration, but its cost structure may become more complex for businesses with multiple connections or frequent data updates. Companies should carefully evaluate how the per - connection MAR billing model will impact their specific use case.

For those looking for a more predictable pricing structure, Weld offers fixed-cost ETL with a clear monthly rate per data source. Choosing the right solution depends on data volume, budget, and business needs — whether you prioritize scalability with Fivetran or predictability with Weld.

Additional resources

For more insights on ETL pricing and data automation, check out these articles:

• Top 10 Fivetran alternatives
• Compare data tools with Weld
• Top 8 data warehouse picks for a modern data stack
• Top 10 Supermetrics alternatives