QuickSight vs Power BI: Pricing, Features, and the Real Difference Between Amazon QuickSight and Power BI
A straight comparison of Amazon QuickSight and Microsoft Power BI, with prices we read from each vendor rather than copied. We build a plain-English analytics tool, so we tell you below exactly where we fit and where we do not.
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Direct answer
A Power BI Pro seat costs $14 per user per month and an Amazon QuickSight Author seat costs $24, so Power BI is cheaper to author, while QuickSight is cheaper for read-only users at $3 per reader or a pooled per-session plan. Power BI is the natural fit if your company runs Microsoft 365 and Azure; QuickSight fits AWS-native teams that want serverless, embedded BI billed by usage. QuickSight also runs entirely in the browser, so it works on a Mac, where Power BI Desktop does not.
Last updated July 2026
›_ side by side
QuickSight vs Power BI, honestly.
| Dimension | QuickSight (Amazon) | Power BI (Microsoft) |
|---|---|---|
| Entry price to author | $24 per user per month (Author, billed annually) | $14 per user per month (Pro, paid yearly) |
| Read-only cost | $3 per reader per month, or a pooled plan of 500 sessions for $250 a month ($0.50 per extra 30-minute session). | Covered by a Pro seat, or by Fabric capacity at scale where readers need no individual license. |
| Authoring app and OS | Fully browser-based, no desktop install, so it runs on Mac, Windows or Linux. | Power BI Desktop, where reports are authored, is Windows only. Mac users need a VM or the limited browser service. |
| Pricing model | Per-role seats plus true consumption: you can pay per reader or per session for occasional viewers. | Per-seat (Pro, Premium Per User) plus Fabric capacity (F-SKUs) for large deployments. |
| Native ecosystem | AWS: Redshift, Athena, S3, RDS and Aurora, with connectors for Snowflake and on-prem. | Microsoft: Excel, Microsoft 365, Azure and Fabric. The default in a Microsoft shop. |
| In-memory engine | SPICE, the QuickSight in-memory store, kept fast without managing servers. | VertiPaq, the columnar engine behind Power BI models. |
| Built-in AI | Amazon Q generative BI in the Author Pro tier ($40 a seat), plus a $250 a month per-account enablement fee. | Copilot for natural-language questions and report drafting. |
| Modeling depth | Simpler to start, but thinner modeling than Power BI and a smaller community. | Deeper modeling through DAX and Power Query, at the cost of a real learning curve. |
| Who it suits | AWS-native teams, mostly-occasional readers, Mac desks, embedded analytics. | Microsoft-centric teams, tight per-author budgets, wide governed rollout. |
Comparison reflects our understanding of publicly available information and is meant to be fair, including where each tool beats us. Vendors evolve; verify the latest before deciding.
›_ what it costs
QuickSight vs Power BI pricing.
| Plan | QuickSight | Power BI |
|---|---|---|
| Free option | No standing free tier (30-day and embedded developer trials) | Free Power BI account with limited sharing |
| Author / creator seat | Author, $24 per user per month, billed annually | Pro, $14 per user per month, paid yearly |
| AI-enabled author seat | Author Pro, $40 per user per month, plus $250 a month per-account fee | Premium Per User, $24 per user per month, paid yearly |
| Read-only user | Reader, $3 per user per month, or 500 sessions for $250 a month | Covered by Pro or by Fabric capacity |
| Capacity / embedded | Session-capacity and embedded plans, priced by usage | Fabric and Embedded capacity (F-SKUs), reserved or pay-as-you-go |
QuickSight prices were read from the AWS QuickSight pricing page on 21 July 2026. Power BI prices were read from Microsoft's pricing page on 21 July 2026. Both vendors change pricing and enterprise deals are negotiated, so confirm current numbers with the vendor before you buy.
›_ the call
Which one should you pick?
01
Choose QuickSight if
Your data already lives in AWS, most of your audience only reads dashboards now and then, or your team is on Macs. The $3 reader seat and the per-session pool make occasional access genuinely cheap, and the browser-only authoring sidesteps the Windows problem entirely. Watch the $250 a month enablement fee if you turn on the generative BI features.
02
Choose Power BI if
You already pay for Microsoft 365, your data lives in Excel, SharePoint or Azure, and you want the cheapest credible author seat at $14. You get deep modeling through DAX and the tightest Office integration on the market. Budget time for someone to learn DAX properly, and remember the authoring app is Windows only.
03
Neither, if the real problem is questions
Both tools assume an analyst builds a dashboard first and everyone else reads it. If your actual bottleneck is that people keep asking one-off questions and waiting days for an answer, another dashboard will not fix that. That is the gap we built Agentsql for, and it is a genuinely different job from what QuickSight and Power BI do well.
What is the difference between QuickSight and Power BI?
The short version is that QuickSight is the AWS-native, pay-by-usage BI tool that runs in a browser, and Power BI is the Microsoft-native, per-seat tool that authors on Windows. Which cloud you already live in decides most of it.
QuickSight bills the way AWS bills: per role and per session. A Reader is $3 a month, or you buy a pool of sessions (500 for $250) so a large, occasional audience costs little. There is no desktop app to install, which is why it works on a Mac and Power BI does not. The trade is thinner data modeling and a smaller community than Power BI has.
Power BI wins on author economics and modeling. At $14 a Pro seat it is cheaper to give people authoring rights, and DAX plus Power Query give you modeling depth QuickSight does not match. The catch is that Power BI Desktop, where that authoring happens, is Windows only, and DAX is a real language you have to learn.
If your stack is AWS, QuickSight is the path of least resistance. If it is Microsoft 365 and Azure, Power BI is. Teams rarely switch clouds to get a BI tool, and they should not.
Is QuickSight cheaper than Power BI?
It depends on who is using it. For read-only viewers, QuickSight is usually cheaper: $3 a reader, or a per-session pool, against Power BI needing a Pro seat or Fabric capacity for wide viewing. For authors, Power BI is cheaper at $14 against QuickSight's $24.
The generative BI features shift the math. QuickSight's Author Pro is $40 a seat and adds a $250 a month per-account enablement fee the moment you switch on Amazon Q, which is easy to miss when you price it. Power BI folds Copilot into its existing tiers.
The honest way to compare is to count your real mix. A deployment that is ten authors and two hundred occasional readers looks very different on the two tools than one that is fifty full-time analysts. Price the shape you will actually have.
Does QuickSight work on a Mac?
Yes. QuickSight is entirely browser-based, with no desktop application to install, so authoring and viewing both work on macOS, Windows or Linux without any workaround.
This is a real advantage over Power BI for Mac-heavy teams. Power BI Desktop, the app you build reports in, is Windows only, so Mac users run it in a virtual machine or Parallels, or work in the browser service with fewer features. For a design, marketing or startup team on MacBooks, that single fact often settles the choice.
Where a third option fits
We build Agentsql, so treat this section as interested rather than neutral. It is here because the QuickSight vs Power BI question often hides a different one.
Both tools are built around the dashboard: someone models the data, builds the view, publishes it, and the business reads it. That is great for the numbers you watch every week. It is poor for the long tail of one-off questions, the "how many trial signups from that campaign actually converted" sort, because every one becomes a ticket for the person who knows the modeling layer.
Agentsql connects read-only to Postgres, MySQL, Snowflake or BigQuery, turns a plain-English question into SQL, runs it, and returns a chart, a table and a one-line answer, with the SQL shown every time so an analyst can check the work. There is no semantic model to build first and no DAX to learn. It starts at $49 a month.
It is not a replacement for either BI tool, and we would rather say so. If you need governed executive dashboards refreshed nightly, buy QuickSight or Power BI. Plenty of teams run a dashboard tool for the standing numbers and something like us for the questions in between.
›_ frequently asked
QuickSight vs Power BI questions, answered.
Is QuickSight better than Power BI?
Neither is universally better. QuickSight is better for AWS-native teams, occasional readers at $3 a seat, and Mac users, because it runs in the browser. Power BI is better for Microsoft shops, cheaper authoring at $14 a seat, and deeper modeling through DAX. Pick the one that matches the cloud and desktops you already run.
Is Amazon QuickSight cheaper than Power BI?
For readers, usually yes: QuickSight Readers are $3 a month or a pooled per-session plan, while wide viewing in Power BI needs Pro seats or Fabric capacity. For authors, Power BI is cheaper at $14 a seat versus $24 for a QuickSight Author. Generative BI adds a $250 a month fee on QuickSight, so price your real user mix.
Does Amazon QuickSight have a desktop app?
No. QuickSight is entirely browser-based, so there is nothing to install and it works on Mac, Windows and Linux. This differs from Power BI, whose authoring tool, Power BI Desktop, is Windows only and needs a virtual machine or the browser service to run on a Mac.
Can QuickSight connect to data outside AWS?
Yes. QuickSight is strongest with AWS sources like Redshift, Athena, S3, RDS and Aurora, but it also has connectors for Snowflake, SQL Server, PostgreSQL, MySQL and on-premises databases. It is optimized for AWS, not locked to it, though the smoothest experience is inside the AWS ecosystem.
Do you need to know SQL to use QuickSight or Power BI?
Not for basic use. Both let you connect data and build visuals without writing SQL. In practice, real work needs modeling: DAX and Power Query in Power BI, calculated fields and dataset prep in QuickSight. SQL knowledge helps once you go past a single clean table, but the language you must learn first is the tool's own modeling layer.
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