Why Your Fivetran Bill Just Doubled (And What to Do About It)
Mike Ritchie
If you use Fivetran and your bill spiked in March 2025, you're not imagining things.
Fivetran changed how it calculates Monthly Active Rows (MAR) from an account-wide total to a per-connector basis. For teams running 10, 20, or 50 connectors (which is most teams), this one change increased costs by 40% to 70%. Some customers reported bills jumping 2x to 4x. A few saw increases of 4x to 8x.
This wasn't a bug. It was a pricing model overhaul. It hit thousands of data teams at the same time.
Here's what happened, why the alternatives everyone is rushing to don't actually solve the problem, and what the real fix looks like.
What Fivetran Actually Changed
Before March 2025, Fivetran calculated MAR at the account level. If you had 500K rows syncing from Salesforce and 300K from Google Ads, your total was 800K MAR. You got volume discounts as your total went up.
After March 2025, each connector is billed independently. That same setup? Now you're paying the rate for 500K MAR on Salesforce and a separate rate for 300K MAR on Google Ads. Volume discounts only apply within each individual connector, not across your account.
The math works out badly for almost everyone:
- Small, distributed setups get hammered. If you have 15 connectors each syncing 50K rows, you're now paying 15 separate bills at the lowest (and most expensive per-row) tier instead of one bill at 750K MAR with better rates.
- Marketing and advertising data is especially painful. Sources like Facebook Ads, Google Ads, and HubSpot have high row churn. Every row that updates counts as "active" again. Under per-connector billing, these become the most expensive connectors to run.
- Bulk discounts vanished. Previously, your 30th connector was cheap because your account-wide volume pushed you into favorable pricing tiers. Now every connector starts at the bottom of its own pricing curve.
Fivetran also killed the Starter plan and started charging for transformations (previously free) based on "successful model runs" above 5,000 per month. So the pricing change wasn't just one thing. It was three things at once.
What Teams Are Actually Paying
The Standard plan now costs $500 per million MAR, per connector. Here's what that looks like in practice:
A mid-market SaaS company with Salesforce (1M rows), HubSpot (500K), Stripe (200K), PostgreSQL (2M), Google Ads (300K), and five smaller sources might have previously paid $1,500 to $2,000/month at account-wide tiering. Under per-connector billing, that same setup runs $3,000 to $5,000/month or more, depending on row churn.
A startup with 8 to 10 connectors and moderate data volumes that was paying $500/month could easily be looking at $1,200 to $1,800/month.
High-volume deployments on Fivetran can hit $15,000 to $30,000/month. One G2 reviewer described costs as "4 to 8x more expensive than alternatives on the market."
Worse: costs are now harder to predict. A spike in row updates on a single connector can blow out your budget with no warning. One Reddit user described a "simple oversight" in their data flow that tripled their bill in a single month.
The G2 Sentiment: Cost Is Now the Top Complaint
The reviews tell the story. On G2, roughly 35% of recent Fivetran reviewers (6 out of 17) now cite cost as their single biggest complaint. That's up significantly from historical reviews, where reliability and ease of use dominated the conversation.
Common themes:
- "The associated cost is not cheap."
- Billing discrepancies between reported usage and actual invoices.
- The new per-connector model makes it "impractical" to scale to more sources.
- Customers feeling locked in because migration is painful.
- Users who built their entire stack around Fivetran now feel trapped: the cost of migrating dozens of connectors to a new tool is enormous, which is exactly what makes the price hike stick.
Nexla published an analysis calling it the "SaaS Pricing Escalation Playbook": land with attractive pricing, expand as customers build dependencies, extract by changing the pricing model, rationalize by claiming the changes benefit customers. Harsh framing, but accurate when you look at the timeline.
This pattern isn't unique to Fivetran. Snowflake, Looker, and Databricks have all followed similar trajectories: generous early pricing that grows into enterprise-grade invoices once you're locked in. But Fivetran's March 2025 change was unusually abrupt. Most pricing increases happen at renewal. This one changed the pricing model itself, mid-contract for many customers.
The Rush to "Cheaper Fivetran" (And Why It Misses the Point)
Every time Fivetran raises prices, a wave of blog posts appears: "Top 10 Fivetran Alternatives." The usual suspects show up. Hevo, Airbyte, Rivery, Weld, Stitch, Meltano. Each positions itself as "Fivetran, but cheaper" or "Fivetran, but open source."
They're not wrong. Many of these tools are genuinely less expensive than Fivetran for comparable connector coverage. Some are significantly cheaper. Some are free if you self-host.
But here's what none of them ask: why are connectors a separate line item in the first place?
Every one of these alternatives accepts the premise that data connectors should be a standalone product with standalone pricing. The debate is always about the price of the ETL tool, never about whether you should be paying for an ETL tool at all.
Think about what connectors actually do. They pull data from your SaaS tools and databases and put it somewhere you can query it. That's it. It's plumbing. The entire data industry has somehow normalized paying $500, $2,000, or $10,000+ per month for plumbing.
Switching from Fivetran to Hevo or Airbyte saves you money. But you still have the same architecture: a connector tool that feeds a warehouse that feeds a BI tool, each with its own bill, its own login, its own support team, and its own pricing model designed to grow faster than your business.
The cheaper version of a broken architecture is still a broken architecture.
This is the part that every "Top 10 Fivetran Alternatives" post skips. They compare features and pricing. They never question the category. And because every company on those lists sells connectors as a standalone product, none of them have any incentive to point out that the category itself is the problem.
The Real Problem: Too Many Bills for One Job
The "modern data stack" promised modularity. Pick the best tool for each layer. Mix and match. Freedom of choice.
In practice, it delivered the Frankenstack: five to seven tools, five to seven vendors, five to seven contracts, a full-time job managing the glue between them.
Here's what a typical mid-market analytics stack costs:
| Layer | Tool | Monthly Cost |
|---|---|---|
| Connectors | Fivetran | $1,500 to $5,000 |
| Warehouse | Snowflake or BigQuery | $500 to $3,000 |
| Transformations | dbt Cloud | $100 to $500 |
| BI / Dashboards | Looker or Metabase Cloud | $300 to $3,000 |
| Semantic Layer | Cube Cloud (maybe) | $0 to $300 |
| Total | $2,400 to $11,800 |
And that doesn't include the engineering hours spent maintaining the integrations between these tools. Or the time debugging why a Fivetran sync broke your dbt models. Or the week you lose when Snowflake and Looker disagree on how to calculate a metric.
The Fivetran price hike is painful. But it's also clarifying. It forces you to look at the total bill for the first time and ask: is this really the best way to do analytics?
What If Connectors Were Just... Included?
This is the question nobody in the "Fivetran alternatives" space is asking, because the answer threatens their entire business model.
At Definite, connectors are included. Not as an add-on. Not as a separate SKU. Included, in the same way that a car includes wheels.
The Definite Platform tier is $250/month. That includes:
- 200+ native data source connectors. Salesforce, HubSpot, Stripe, Google Ads, PostgreSQL, MySQL, Shopify, and hundreds more. All included.
- A built-in data warehouse powered by DuckDB and DuckLake. No Snowflake bill. No BigQuery bill. Sub-second queries on data that would take minutes in legacy warehouses.
- BI and dashboards. Build, share, and embed dashboards. No per-viewer fees. No seat math.
- A semantic layer. Define your metrics once in YAML; they're consistent everywhere.
- Fi, an AI analyst. Ask questions about your data in plain English. Not bolted on, built in from day one.
- Unlimited storage. Unlimited users.
The comparison isn't Definite vs. Fivetran. It's $250/month for the whole stack vs. $2,400 to $11,800/month for pieces of a stack that you then have to glue together yourself.
When You Still Need Standalone ETL
Definite doesn't replace Fivetran for every use case. There are legitimate scenarios where standalone ETL makes sense:
- You need CDC (Change Data Capture) from production databases at extremely high volumes with sub-minute latency. Fivetran's CDC connectors for Oracle, SQL Server, and PostgreSQL are genuinely excellent for this.
- You're deeply embedded in the modern data stack with years of dbt models, Snowflake optimizations, and Looker views. Ripping it all out is a multi-quarter project. Swapping Fivetran for a cheaper alternative might be the pragmatic short-term move.
- You have compliance requirements that mandate specific data residency or processing controls that only certain vendors can meet.
- You need 500+ connectors, including niche or industry-specific ones that aren't in every library.
But most teams? Most teams have 10 to 30 connectors, moderate data volumes, and a BI tool that three people actually use. They don't need a $5,000/month connector bill. They don't need a separate warehouse bill. They don't need to pay a different vendor for every layer of their stack.
They need their data in one place, queryable, with dashboards their team will actually look at. That's it.
Here's a simple litmus test: if your total connector bill is more than your BI tool costs, you're paying too much for plumbing. And if your connector bill, warehouse bill, and BI bill together exceed $1,000/month, you should seriously evaluate whether a single platform could replace all three.
The Fivetran-dbt Merger Makes This Worse
In October 2025, Fivetran and dbt Labs announced an all-stock merger, branding it as the future of "open data infrastructure."
This matters for pricing because it reduces your negotiating leverage. Fivetran and dbt were previously independent products you could swap out separately. Now they're one company. If you want to leave Fivetran, you're also leaving dbt (or at least the tightly integrated version). The switching cost just doubled.
Every consolidation in the modern data stack makes the case for all-in-one platforms stronger. Not because integration is inherently better than modularity, but because the vendors selling you modularity keep merging into monoliths anyway. At least with a purpose-built platform, you get the integration without the bolted-together pricing.
What to Do Right Now
If your Fivetran bill just spiked, here's the decision tree:
1. Audit your actual usage. Log into Fivetran and look at MAR per connector. You'll probably find connectors syncing data nobody queries. Turn those off first. This alone can cut your bill 20% to 30%.
2. Ask whether you need standalone ETL. If you're running fewer than 30 connectors with moderate volumes (under 5M total rows), you probably don't. You need an analytics platform that includes connectors.
3. If you do need standalone ETL, negotiate hard. Fivetran is losing customers right now. They'll offer discounts if you push. Alternatively, look at Airbyte (open source, free to self-host), Hevo (cheaper managed option), or Meltano (code-first, free).
4. If you don't need standalone ETL, stop paying for it. Move your connectors and your warehouse and your BI into one platform. Eliminate the ETL line item entirely.
Definite gives you a full analytics stack (connectors, warehouse, BI, AI, semantic layer) for $250/month. That's less than most teams pay for Fivetran alone. No per-row pricing. No per-connector billing. No surprise invoices.
See what Definite can do for your team.
The Fivetran pricing change isn't an anomaly. It's the logical endpoint of a model where every layer of your data stack is a separate profit center with its own incentive to charge more.
The alternative isn't a cheaper connector tool. It's a platform where connectors are a feature, not a product. Where the warehouse, the BI layer, and the AI are all one thing. Where you pay one bill, open one app, and get answers.
That's what we built Definite to be.
Try Definite free and go from raw data to live dashboards in under 30 minutes.
- See connectors: definite.app/connector-db
- View pricing: definite.app/pricing