Power BI Embedded bills by consumption.
One busy month and your invoice triples.
Power BI has excellent visualizations and deep Microsoft ecosystem integration. For ISVs embedding analytics in a customer-facing product, the core problem is the billing model: A SKU pricing scales with usage — and usage is controlled by your customers, not you. A traffic spike, a product launch, a big customer's busy quarter — your cost goes up. When you can't predict the bill, you can't build a stable business model around it.
Why consumption billing breaks down for ISVs
The model that works for internal enterprise BI creates a structural problem when your customers' usage determines your cost.
Your customers control your cost
When a large customer has a busy quarter, their dashboard usage climbs. Your Power BI Embedded bill climbs with it. That's not a cost you can predict, control, or cleanly pass through in your pricing. Your gross margins are determined in part by how much your customers choose to use their analytics — and you have no say in that number.
Traffic spikes become invoice spikes
A product launch, a major customer campaign, a viral feature — these events drive analytics traffic up fast. With flat pricing, growth is pure upside. With A SKU billing, a good month creates a surprise invoice. A SKUs don't throttle — they scale, and you pay for every render. One excellent quarter can blow your unit economics for the year.
Azure lock-in — your reports don't travel
Power BI reports, data models, and workspace configurations use native Power BI formats tied to the Azure stack. If you need to change platforms, move infrastructure, or reduce Microsoft dependency, you're not migrating configuration — you're rebuilding your entire analytics layer from scratch. The exit cost isn't theoretical; it's a full re-implementation of every embedded report your customers use.
Fabric migration adds a hidden licensing trap
Microsoft retired P SKUs in July 2024 and is steering ISVs toward Fabric F SKUs as the modern option. The trap: F SKUs below F64 (F8, F16, F32) require Power BI Pro licenses at $14/user/month for end users in most embedding scenarios. An ISV with 500 end users on an F8 capacity ($625/month) would add $7,000/month in user licensing — making the 'affordable' tier dramatically more expensive. A SKUs avoid this, but carry hourly consumption billing.
Power BI Embedded vs Yurbi — for ISVs
Evaluated on the dimensions that matter for a customer-facing embedded analytics product.
Power BI Embedded A SKU pricing sourced from Microsoft Azure pricing page and community-verified figures (2025). Yurbi pricing from yurbi.com/pricing/. A SKU costs are billed hourly; annual commitment reservations available at a discount.
Power BI Embedded vs Yurbi — direct answers
Power BI Embedded uses Azure A SKUs — capacity-based tiers billed hourly. A1 runs approximately $750/month at continuous use. A2 runs approximately $1,500/month. A3 runs approximately $3,000/month. You pay for the capacity tier you're running, not a fixed number of users. As your customers' usage grows, you need larger capacity tiers to avoid throttling — meaning your costs scale with behavior you don't control.
Yurbi charges a flat annual rate: $10,000/year (Starter, up to 75 users), $18,000/year (Growth, up to 250 users), $24,000/year (Scale, up to 500 users), $30,000/year (Unlimited). Same price whether your customers run 10 reports or 10,000. See yurbi.com/pricing for the full breakdown.
Microsoft retired P SKUs for new customers in July 2024, replacing them with Microsoft Fabric F SKUs. There's some good news for ISVs on A SKUs: Microsoft walked back the plan to force A SKU users into Fabric. A SKUs are preserved for external-user embedding without per-user licensing requirements.
The concern is for ISVs being steered toward Fabric F SKUs as the "modern" option. F SKUs below F64 — including F8, F16, and F32 — require Power BI Pro licenses at $14/user/month for end users in most embedding scenarios. An ISV with 500 end users on F8 capacity ($625/month) would add $7,000/month in user licensing on top of capacity costs. That's a significant hidden cost that doesn't appear in the SKU headline price. If you're evaluating Fabric today, understand the full licensing stack before committing.
Power BI Embedded is an Azure cloud service — it cannot run on-premise or on your customers' servers. Power BI Report Server is a separate Microsoft product that runs on-premise, but it's not the same product, has significant feature limitations versus Power BI Embedded, and is not designed for ISV multi-tenant embedding at scale.
If your customers have data residency requirements, private cloud mandates, or on-premise security policies — Power BI Embedded cannot meet those requirements. Your entire embedded analytics deployment lives on Microsoft's cloud infrastructure. Yurbi is self-hosted only: Windows, Linux, or Docker on your own infrastructure or your customers'. Your data never passes through our servers.
Power BI has a broader chart library and more polished default visualizations than Yurbi — that's accurate and worth acknowledging. The question for ISV embedding is whether that difference matters for your specific product. Most customer-facing embedded analytics products use 8–12 chart types that cover the substantial majority of end-user needs. Yurbi has 20+ chart types and a custom visualization API for cases where you need something specific.
If your core value proposition depends on AI-generated insights, natural language query, or Microsoft Copilot integration — Power BI has a real and meaningful lead that's worth the trade-offs. If your core need is multi-tenant self-service analytics with predictable cost and self-hosted deployment, Yurbi is purpose-built for that. The visualization gap matters less than it appears when the billing model is structurally wrong for your business.
Being direct: Yurbi has no AI or Copilot analytics features yet — that's on the roadmap. Fewer visualization types than Power BI's full library. No native Microsoft 365, Teams, SharePoint, or Azure integration. Embedding is iframe and API only — no JavaScript SDK for deeply programmatic in-page interactivity. SSO is session-token based via our DoLogin API, not SAML or OIDC. Dashboard interactivity uses global filters and drill-down, not associative click-through filtering between widgets. Mobile is functional but not a differentiating feature. ARM architecture not currently supported.
We'd rather you know these things now than discover them post-implementation. Tell us in a demo and we'll give you an honest fit assessment rather than work around the question.
Using Power BI for your internal team's analytics is a fundamentally different decision than embedding it in a product your customers pay for. Internal BI has predictable usage, single-tenant requirements, and a simpler billing relationship where your own team's behavior drives cost. Customer-facing embedded analytics has unpredictable usage patterns, multi-tenant isolation requirements, and the consumption billing problem described on this page.
Your internal Power BI investment doesn't obligate you to use Power BI Embedded externally. Many ISVs use Power BI internally for their own operations and a separate embedded analytics platform for their customer-facing product. The evaluation criteria are genuinely different — don't let internal familiarity be the deciding factor for a customer-facing infrastructure decision.
The honest answer: more work than switching between similar platforms, less than people initially fear. Power BI reports (.pbix files) use a proprietary format that doesn't migrate directly to Yurbi — you're rebuilding your report library in Yurbi's interface. For most ISVs with a defined set of customer-facing reports, that's a contained rebuild, not an open-ended project. Your data doesn't move because Yurbi queries your existing databases directly.
The pattern we see: ISVs run a Yurbi trial alongside their existing deployment, rebuild their top reports as a validation test, and cut over on their next renewal cycle. Download the trial and test with your actual data — that's a faster way to scope migration effort than any comparison document.