Domo vs Power BI: Pricing, Cost Per User and Which One a Mid-Market Team Should Buy

Domo and Power BI both sell business intelligence to mid-market companies, and they are impossible to compare on price, because only one of them has a price. Microsoft publishes $14.00 per user per month for a Power BI Pro seat. Domo publishes nothing at all, and has gone further than that: it has abolished per-user charging entirely. Its own words are that the credit model "replaces our previous cost and usage models, including per-seat pricing", and that "user seats are free for everyone in your organization".

So the honest framing is not which tool is cheaper. It is that these two vendors bill different nouns. Power BI bills people. Domo bills activity. Which one costs you less depends on a ratio inside your own company, and this article works out where that line sits. Every Domo quotation was read from domo.com on 8 September 2026, and the Microsoft figures were verified on 2 September 2026.

Domo vs Power BI: the short answer

Power BI is cheaper for a small team that needs a lot of analysis and has a modest data pipeline. Domo is cheaper for a company that wants a large number of people reading dashboards and can keep its refresh schedules calm. The break point is read-only users: Power BI charges full price for a person who never builds anything, and Domo charges nothing for that person at all. If you have more than about 100 viewers, Power BI's viewer bill starts to dominate every other line item.

How much does Domo cost compared to Power BI?

Power BI publishes two seat prices and one capacity price. Pro is $14.00 per user per month, Premium Per User is $24.00, and capacity SKUs are priced separately in Microsoft Fabric. Domo publishes no price of any kind. Its pricing page offers a 30-day free trial and a "Custom Pricing" tier reached by booking a demo, and the markup on that page carries zero dollar amounts. We checked rather than assumed: across all five of Domo's pricing URLs there are exactly five dollar figures in total, and not one is a credit price, a plan price or a seat price.

What Domo does publish is the meter. Credits are consumed at one per table created or updated, one per dataflow execution, one per million Domo-managed materialized rows per month, and fractional credits per AI interaction. You can estimate your own consumption from those rules with decent accuracy. What you cannot estimate is what a credit costs, which is the number you have to extract from a sales call.

The seat comparison, at three company sizes

The right-hand column is the whole argument. Domo's line does not move when the company grows, because Domo explicitly lists "Size of your team" among the things that do not affect your bill, alongside the "Number of cards, dashboards, or apps" you build.

Does Power BI charge for read-only users?

Yes, and this is the detail that decides most Domo versus Power BI evaluations. Microsoft's own documentation states that "all SKUs other than P and F64+ require a Pro or Premium Per User (PPU) license, or a Power BI individual trial to consume Power BI content". Consume, not create. A regional manager who opens one dashboard on Monday morning and touches nothing else needs the same $14.00 seat as the analyst who built it.

There is a capacity escape, and it is expensive. The first Fabric SKU that frees your viewers from needing a seat is F64, which lists at roughly $60,032 a year reserved. That is the equivalent of 357 Pro seats, so it only starts making sense for organizations well past the mid-market. Below that threshold, every single reader is a billable line.

Domo inverts this completely. Read access is free at any headcount, which is the entire pitch of its consumption model and, to be fair to Domo, a genuine one. If your problem is that finance has restricted dashboard access to save on licenses, Domo removes that problem outright.

What actually drives a Domo bill?

Refresh frequency, by a wide margin. Because ingestion and transformation are both metered per execution rather than per gigabyte, the schedule you pick is the largest number in the whole calculation. Take an ordinary setup of 40 source tables and 15 dataflows and change nothing except cadence.

Same data, same dashboards, same people. Nothing about the business changed, and consumption moved by a factor of 96. Power BI has no equivalent exposure: a Pro seat costs $14.00 whether the underlying dataset refreshes once a day or eight times, subject to the refresh limits built into the license rather than a meter.

That asymmetry is the practical risk in choosing Domo, and it is worth being blunt about it. You are trading a bill you can count in advance for one you have to forecast, from a vendor that will not tell you the unit rate. Teams that already track consumption-based spend across their stack handle this well; teams treating it as a flat SaaS subscription tend to be surprised at renewal. If you are moving several tools onto usage-based billing at once, it is worth putting proper visibility over your cloud and SaaS spend in place before the first invoice rather than after it.

Which is better for a company that already has a data warehouse?

Domo, on cost, and by a wider margin than most comparisons acknowledge. Domo states that if you already run a cloud data warehouse "such as Snowflake, BigQuery, or Databricks" and "Domo doesn't manage it, there's no charge for data". Storage is only billed when Domo holds it, at one credit per million materialized rows per month, or one credit per two million virtual rows.

So a company with an existing Snowflake account can run Domo with an entire cost factor switched off. That is a real structural advantage and it is easy to give away by accident, because the path of least resistance during implementation is to materialize everything into Domo. If you go this route, make sure the proposal reflects your storage staying yours rather than quietly assuming Domo-managed storage.

Power BI's equivalent question is different in kind. Power BI Desktop requires "Windows 10 or Windows Server 2016 or later", and Microsoft states that "Citrix VDI and other virtual desktop environments, excluding Azure Virtual Desktop and Windows 365, aren't supported". If your analysts are on Macs, that is a constraint no amount of budget solves neatly, and it is the reason a lot of design-led and startup teams rule Power BI out before price ever comes up.

Domo vs Power BI vs Tableau: where each one lands

Tableau deserves a caveat here. It publishes no price for the Creator, Explorer and Viewer roles at all, only three edition entry prices marked "starting at", so the widely quoted $75 Creator seat is a reseller figure rather than a Tableau one. The detail matters if you are building a three-way business case. The full working is on our Tableau pricing page, and the two platforms sit head to head in Domo vs Tableau.

How do you decide between them?

Count two things about your own company and the answer usually falls out.

The first is your ratio of readers to builders. If 80 percent of the people who need data will only ever open a dashboard someone else built, Power BI is charging you full retail for the cheap half of your organization, and Domo charges nothing for it. At 200 people with 20 real analysts, Power BI's viewer bill alone is $30,240 a year, and that number buys read access and nothing else.

The second is your pipeline temperament. Count your tables and dataflows, multiply by the schedules you genuinely need rather than the ones you would set by default, and you have your Domo credit consumption. If that number is modest, Domo's free seats are close to a free lunch. If you run hourly refreshes across a hundred objects because somebody once asked for fresher numbers, you are buying the expensive side of a 24x multiplier and Power BI's flat seat starts to look like the safer purchase.

Neither answer is available from a rate card, which is the frustrating and honest conclusion. Domo will not publish a credit price, so you have to run the 30-day trial against your real sources, read the Credit Utilization interface, and take your own consumption number into the negotiation. That is more work than reading a pricing page, but it puts you in a stronger position than any published rate would have. The full breakdown of the meters is on our Domo pricing page, and the Microsoft side is worked out in Power BI pricing.

A third option worth pricing

Both of these are platforms, and a lot of teams evaluating them do not actually have a platform problem. They have a queue problem: the data already sits in a warehouse that works fine, and the people who need answers cannot get them without filing a request and waiting two days. Buying an ingestion-metered platform or a seat for every reader are both expensive ways to solve a question-asking problem.

That is the case Agentsql is built for. It connects read-only to the Postgres, MySQL, Snowflake or BigQuery database you already run, turns a plain-English question into SQL, executes it, and shows the query next to the answer so an analyst can verify the logic. Nothing is ingested and nothing is copied, so there is no execution meter to manage and no viewer seat to buy. Our pricing is a single published monthly figure, which after an article about two vendors whose real cost you cannot look up feels worth stating plainly.