How BerryBox cut embedded analytics costs
while scaling.
BerryBox faced the same cost escalation trap with embedded analytics. See how they switched to DataBrain and achieved predictable pricing at scale.
Discover pricing models, licensing options, & factors that influence the cost of Power BI. Make informed decisions about your analytics investment with us.
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We've helped SaaS teams migrate from Power BI Embedded to DataBrain. The #1 reason? Hidden costs. The SKU pricing looks manageable until you factor in Azure infrastructure, Pro licenses for content creators, and the 2-4 weeks of developer time just for basic embedding. Here's the real cost picture.
If you're evaluating Power BI Embedded pricing for your SaaS product or enterprise application, the sticker price is only half the story. Microsoft's pricing model is capacity-based, which sounds flexible until you realize how quickly costs compound as your user base grows.
This article breaks down every cost you'll actually encounter in 2026, from Fabric F-SKUs to the hidden fees most teams discover too late. We'll also compare Power BI Embedded against alternatives so you can decide what's genuinely worth the investment.
Microsoft has shifted its embedded analytics pricing toward Microsoft Fabric F-SKUs as the primary option. Legacy A-SKUs still work but are no longer the recommended path for new deployments. Here's the current landscape.
Fabric F-SKUs are capacity-based subscriptions that include access to the full Microsoft Fabric platform, not just Power BI. Pricing is based on Capacity Units (CU), billed through Azure. (See current pricing on the Azure Fabric pricing page.)
SKU Capacity Units Approx. Monthly Cost Equivalent Legacy SKU Best For
| Tier | Capacity Units | Price | Power BI Equivalent | Best For |
|---|---|---|---|---|
| F2 | 2 CU | $262/mo | — | Dev/test environments |
| F4 | 4 CU | $524/mo | — | Small pilot apps |
| F8 | 8 CU | $1,048/mo | EM1/A1 | Small production apps |
| F16 | 16 CU | $2,096/mo | EM2/A2 | Mid-market SaaS |
| F32 | 32 CU | $4,192/mo | EM3/A3 | Growing applications |
| F64 | 64 CU | $8,384/mo | P1/A4 | Enterprise / ISV |
| F128 | 128 CU | $16,768/mo | P2/A5 | Large-scale deployment |
Prices are pay-as-you-go rates for US regions as of March 2026. Verify current rates for your region on the Azure pricing calculator.
Important licensing nuance: Viewer licensing depends on your embedding scenario:
If you're building customer-facing analytics — the most common SaaS use case — the F64 threshold does not affect your end-user licensing costs. Your costs are driven by capacity (how much compute you need), not by how many customers view dashboards.
A-SKUs are billed hourly through Azure and can be paused when not in use. Microsoft has confirmed that A-SKUs are not being deprecated (unlike P-SKUs), so they remain a valid option for teams that want simple hourly billing.
Node vCores RAM Price/Hour Monthly (24/7) Monthly (12hrs/day)\
| SKU | v-Cores | Memory | Hourly Price | Monthly Price | Approx. Paused Cost |
|---|---|---|---|---|---|
| A1 | 1 | 3 GB | $1.01/hr | $735/mo | ~$370/mo |
| A2 | 2 | 5 GB | $2.01/hr | $1,470/mo | ~$735/mo |
| A3 | 4 | 10 GB | $4.02/hr | $2,940/mo | ~$1,470/mo |
| A4 | 8 | 25 GB | $8.06/hr | $5,880/mo | ~$2,940/mo |
| A5 | 16 | 50 GB | $16.12/hr | $11,850/mo | ~$5,925/mo |
| A6 | 32 | 100 GB | $32.25/hr | $23,700/mo | ~$11,850/mo |
Cost-saving tip: Pause A-SKUs during off-hours. Running an A1 node only 12 hours per day cuts your bill roughly in half — from $735 to about $370 per month.
Beyond capacity SKUs, you'll need licenses for content creators and administrators:
This is where Power BI Embedded pricing gets uncomfortable. Even with free viewer access in app-owns-data scenarios, the pattern we've seen across dozens of teams follows a predictable trajectory: what starts as a small line item for report creators compounds fast as your analytics ambitions grow.
Year What Happens Annual Cost
| Year | Configuration | Estimated Annual Cost |
|---|---|---|
| Year 1 | F2 capacity + 3 Pro licenses for report creators | ~$3,650/yr |
| Year 2 | Upgrade to F8 for production + 5 Pro licenses | ~$13,420/yr |
| Year 3 | Growing dashboards, need F32 + 8 Pro licenses + Azure infra | ~$52,700/yr |
| Year 4 | Scale demands F64 + 12 Pro licenses + gateway infra | ~$103,000/yr |
How BerryBox cut embedded analytics costs
while scaling.
BerryBox faced the same cost escalation trap with embedded analytics. See how they switched to DataBrain and achieved predictable pricing at scale.
SKU pricing is just the starting point. Here are the costs that consistently surprise teams:
This is the question every team gets stuck on. Here's the decision framework:
| Factor | Power BI Pro | Power BI Premium (Fabric) | Power BI Embedded |
|---|---|---|---|
| Monthly Cost | $14/user | From $8,384/mo (F64) | From $262/mo (F2) |
| Best For | Small internal teams | Large orgs (500+ users) | SaaS / external users |
| Viewer Licensing | Per-user required | Included at F64+ | Free (app-owns-data) |
| White-Labeling | None | Limited | Iframe-based |
| Pause/Resume | N/A | Yes (F-SKUs) | Yes (A-SKUs & F-SKUs) |
| Decision Rule | <25 internal users | 500+ internal users | Customer-facing SaaS |
Quick rule of thumb: If you're embedding analytics into a product your customers use, Embedded (app-owns-data) is the only real option — and your end users won't need individual licenses. If you're distributing reports to internal employees, Fabric capacity (F64+) makes sense once you cross ~50 users.
Power BI Embedded uses iframes for embedding. That means your dashboards look like Power BI inside your product, not like a native part of your application. Microsoft branding can't be fully removed, performance depends on Microsoft's infrastructure, and you lose control over the end-user experience.
For SaaS companies where analytics is a core feature, this is a serious limitation. Your customers will notice the iframe loading lag, the inconsistent styling, and the occasional Power BI error messages that surface in your UI.
This is one of the primary reasons teams migrate to native SDK-based solutions. DataBrain offers true white-labeling where dashboards are indistinguishable from the rest of your product — see how in our DataBrain vs Power BI comparison.
If Power BI Embedded's pricing or limitations don't fit, here are the leading alternatives across different pricing models:\
| Tool | Pricing Model | Starting Price | White-Label | Multi-Tenant | Time to Embed |
|---|---|---|---|---|---|
| DataBrain | Fixed / predictable | Contact sales | Full native SDK | Built-in RLS | 1-2 weeks |
| Tableau Embedded | Per-user | $70/user/mo (Creator) | Limited | Manual | 4-8 weeks |
| Sisense | Enterprise license | Contact sales | Yes | Yes | 8-14 weeks |
| Looker | Enterprise license | Contact sales | Yes | Yes | 4-8 weeks |
| Superset | Open source | Free (OSS) | Limited | Manual | 2-4 weeks |
| Metabase | Open source + Cloud | Free (OSS) / $500+/mo | Limited | Manual | 2-4 weeks |
The pricing models matter more than the sticker prices:
For a deeper dive, see our comprehensive Power BI Embedded alternatives comparison.
How Epochos shipped customer-facing analytics 10x faster.
Epochos needed embedded analytics without the iframe headaches or unpredictable costs. See how they went live with DataBrain in a fraction of the time.
If you're committed to Power BI Embedded, here are actionable strategies to keep costs under control:
Power BI Embedded is a capable platform, and the right choice for teams already deep in Microsoft cloud or with predictable internal-user analytics needs. For customer-facing SaaS analytics, the evaluation moment is typically when capacity costs cross F32 ($4,192/mo) and the cumulative line items (Azure gateway VM hosting, Pro license sprawl past the April 2025 hike, ongoing CU-throttling overhead, and the engineering-week cost of all of the above) push the all-in number past $80K/year.
What's worked for SaaS teams that switched off Power BI Embedded comes down to a few specifics: predictable flat-rate pricing on a published per-tenant rate card, native SDK embedding without iframes, built-in multi-tenancy paired with row-level security, and managed infrastructure they don't have to operate. EpochOS replaced Power BI for predictable pricing and AI / natural-language analytics aimed at their mortgage brokers, and they went live in 2 weeks while saving $100K. BerryBox replaced a Power BI setup their Lead Engineer Arvind Iyer described as "a nightmare," saving $250K and 6–8 months of engineering.
See how DataBrain compares to Power BI Embedded if F32 capacity is on your horizon.
Pricing information in this article is based on publicly available Microsoft documentation and Azure pricing pages as of March 2026. Actual costs vary by region, currency, and Microsoft agreement terms. Always verify current pricing on the Azure Fabric pricing page and Azure Power BI Embedded pricing page before making purchasing decisions.
The minimum cost is $262/month for a Fabric F2 SKU (pay-as-you-go). Legacy A-SKU pricing starts at roughly $1.01/hour (about $735/month if running 24/7, or ~$370/month at 12 hours/day). You'll also need Power BI Pro licenses at $14/user/month for anyone who creates or publishes reports. For customer-facing (app-owns-data) embedding, your end users do not need individual licenses at any capacity tier.
Microsoft offers a free trial to test features, but there is no free tier for production use. You'll need at least one capacity SKU and one Pro license for report creation.
Premium is designed for internal enterprise reporting (employees accessing dashboards). Embedded is built for external or customer-facing analytics (your users accessing reports inside your app). Microsoft is retiring Premium P-SKUs in favor of Fabric F-SKUs, which support both scenarios. The key difference is the embedding model: "user owns data" (internal) vs. "app owns data" (external SaaS).
No , in the "app owns data" scenario (the standard approach for SaaS products), your end users do not need any Power BI license. The capacity subscription covers all viewer access regardless of which F-SKU tier you choose. This is a common misconception. (Source: Microsoft Learn)
The top alternatives include DataBrain (fixed pricing, native white-label), Metabase (open source, self-hosted), Sisense (enterprise-grade), Looker (Google ecosystem), and Apache Superset (open source). Your choice depends on pricing model preference, white-labeling needs, and how quickly you need to ship. See our full alternatives comparison.
Get it touch with us and see how Databrain can take your customer-facing analytics to the next level.
