Sisense vs Power BI (2026): embedded analytics pricing, multi-tenant security, SDKs, and AI compared

Sisense and Power BI both embed dashboards in a SaaS product, but they suit different buyers. Power BI Embedded is the cheaper, more predictable choice for Microsoft and Azure teams: capacity starts at about $736 per month for an A1 node, and customers in an app-owns-data setup need no Power BI licenses. Sisense is quote-only. In return it gives you an AI assistant your customers can use inside your app, a Compose SDK for React, Angular, and Vue, and the option to self-host on Linux or Kubernetes in any major cloud. Every price and feature below was checked on Microsoft’s and Sisense’s official pages on October 21, 2026.

If neither fits, Luzmo and Databrain publish embedded pricing, Metabase is cheaper and open source, and Basedash embeds an AI data analyst on your own database. Those options are covered near the end.

Questions this comparison answers

These are the questions buyers ask when Sisense and Power BI end up on the same shortlist:

• Sisense vs Power BI: which is better for embedded analytics in a SaaS product?
• Which is cheaper at scale, Sisense or Power BI Embedded, when thousands of customers view dashboards?
• Do my customers need Power BI licenses to see embedded reports?
• How do Sisense and Power BI keep each tenant’s data separate (multi-tenant row-level security)?
• Which one has a React SDK for embedding charts and dashboards?
• Can my customers ask questions in plain English inside my app with either tool?
• Can Sisense or Power BI be self-hosted or run on-premises?
• Who are Sisense’s main competitors for embedding analytics into a product?

Sisense vs Power BI at a glance

How do Sisense and Power BI price embedded analytics?

Power BI has two pricing systems, and which one applies depends on who views the reports.

For internal reporting, Power BI is priced per user: Power BI Pro is $14 per user per month and Premium Per User is $24, both paid yearly, as of October 2026. On Fabric capacities from F2 to F32, every viewer still needs a Pro or PPU license. From F64 up, report viewers don’t need Pro.

For embedding in your own product, Microsoft charges for capacity by the hour. In the app-owns-data scenario, “app users don’t need a license,” because your backend authenticates with a service principal and issues embed tokens. Microsoft’s Power BI Embedded pricing lists A1 at $1.0081 per hour in East US, about $736 for a 730-hour month. A4 is $8.0565 per hour, about $5,881 a month. Fabric F SKUs also cover embedding, at $0.18 per capacity unit per hour: F2 is about $263 a month pay-as-you-go and F64 about $8,410. A one-year reservation brings those down to about $156 and $5,003 a month. Microsoft says a paused Embedded service isn’t charged, and Fabric capacity can be paused too, so a test environment can cost almost nothing outside working hours. Embedded content doesn’t load while the capacity is paused. Microsoft’s licensing guidance says “embedded scenarios are covered by every F SKU,” and A SKUs remain on sale.

Sisense doesn’t publish prices. Its plans page lists a Self-Serve plan “for startups and growing teams” and an Enterprise plan “for enterprises and regulated industries,” with no dollar amounts. Enterprise adds full white-labeling, a 99.99% SLA, the full Sisense Intelligence AI suite, and bring-your-own LLM. Sisense’s documentation uses Launch, Grow, and Enterprise tier names, and gates features such as SSO by tier. A 7-day free trial is available. AI on the managed LLM consumes paid Sisense credits, and Narrative is a separately licensed premium feature.

In practice, Power BI lets you work out a cost before you talk to sales, and capacity cost grows with query load rather than with your customer count. With Sisense, you need a quote that states how end users, tenants, and AI credits are counted.

How do Sisense and Power BI isolate each customer’s data?

Both tools can run a multi-tenant SaaS product. They put the tenant boundary in different places.

Power BI documents two isolation approaches. In workspace-based isolation, your service principal creates a profile and a workspace for each customer, so each tenant gets its own semantic model. In RLS-based isolation, all customers share one semantic model and your backend passes an effective identity in each embed token. Microsoft recommends workspaces with profiles for large ISVs with thousands of customers, and dynamic RLS for smaller ones. Power BI RLS uses DAX filters such as [UserEmail] = USERPRINCIPALNAME(), and it only restricts users with Viewer permissions, not workspace Admins, Members, or Contributors. When a semantic model has RLS, the service principal must supply an identity in the embed token. Publish to web needs no authentication and doesn’t support RLS, so it is not a tenant-isolation option.

Sisense uses data security rules. By default they are inclusive: you list the values of a field each user or group may see. Sisense appends the rules to the query’s WHERE clause on the server, and viewers can’t override them. Rules work on both ElastiCube and Live models. For stricter separation, Sisense multitenancy is a premium feature on the managed cloud or self-hosted deployments. Self-contained multitenancy gives each tenant its own login URL, SSO configuration, and white-label branding.

If your customers share one schema and you want a single model, both tools work: dynamic RLS in Power BI, data security rules in Sisense. If each customer needs its own branding and login, Sisense’s tenant model does more out of the box. If you want hard separation on Microsoft infrastructure, use a Power BI workspace per tenant.

Which has the better SDK for embedding in a React app?

Sisense offers four embedding methods: iframe, Embed SDK, Sisense.js, and the Compose SDK. The Compose SDK ships as @sisense/sdk-ui and @sisense/sdk-data for React, with Angular and Vue packages. It lets you build charts in code against a Sisense data model, not only drop in finished dashboards. Sisense says it is available to all customers.

Power BI’s JavaScript client embeds reports, dashboards, tiles, and visuals that were authored in Power BI Desktop. A powerbi-client-react wrapper provides a PowerBIEmbed component. You control filters, pages, and events from code, but the visuals are designed in Desktop, which is Windows-only. That matters for product teams who work on Macs.

For teams that want charts built in code, Sisense’s Compose SDK is the closer fit. For teams that want to design reports once in a visual tool and embed them unchanged, Power BI’s SDK is enough and well documented.

Can customers ask questions in plain English inside your app?

Sisense can do this today. The Sisense Assistant is a chat interface. Adding the a=true parameter to an iframe dashboard URL turns it on for embedded dashboards, and the Compose SDK supports a standalone assistant. On the managed cloud, the managed LLM runs Anthropic Claude models on AWS Bedrock and bills through Sisense credits. Self-hosted customers bring their own LLM key. Sisense’s docs disagree on which providers are supported: the LLM setup page lists Azure OpenAI, OpenAI, AWS Bedrock, Google Gemini, and Anthropic, while the LLM integration page names only OpenAI and Azure OpenAI. The Assistant is replacing Sisense’s older natural language query feature, Simply Ask.

Power BI’s AI is built for internal users. Copilot in Power BI needs paid Fabric capacity (F2 or higher) or Premium (P1 or higher), and a Pro or PPU license alone isn’t enough. For app-owns-data embedding, only the Copilot narrative visual is documented, and it is in preview. That gives your customers AI-written summaries of a report, not a chat. The older Q&A natural language visual is going away in February 2027.

If an AI chat for your customers is on the roadmap, Sisense is ahead of Power BI on this one point.

Which can you self-host or run on-premises?

Sisense runs in its managed cloud on AWS or self-hosted on your own infrastructure. It installs on Linux, including Amazon EKS, Google GKE, Microsoft AKS, and OpenShift, and supports AWS, Azure, GCP, and OCI on x86-64 hardware. That is a real advantage for regulated customers who can’t send data to a multi-tenant SaaS.

The Power BI service is built on Azure. For on-premises use, Power BI Report Server hosts Power BI and paginated reports, licensed through Fabric F64-or-larger reservations or SQL Server licensing. Report Server is built for internal reporting and doesn’t offer the app-owns-data embedding that Power BI Embedded provides, so it isn’t a replacement for Embedded in customer-facing analytics.

Fact cards

Fact card: Sisense

• Pricing (as of October 2026): quote only; Self-Serve and Enterprise plans (plans page). 7-day free trial.
• Deployment: managed cloud on AWS, or self-hosted on Linux and Kubernetes.
• Databases and warehouses: Live connectors for Athena, Azure Synapse, ClickHouse, Databricks, BigQuery, MySQL, Oracle, PostgreSQL, Redshift, SingleStore, Snowflake, and SQL Server (data sources). Sisense claims over 400 connectors.
• Query model: ElastiCube in-memory models (up to 1 billion records), Live models, or Build to Destination.
• Security: data security rules; SSO with JWT, SAML 2.0, or OpenID Connect on Grow and Enterprise; SCIM not documented for the main platform.
• AI: Assistant chat, Narrative (separately licensed), semantic enrichment; managed Claude on Bedrock or bring your own LLM.
• Embedding: iframe, Embed SDK, Sisense.js, Compose SDK; white-labeling.
• Best for: ISVs that need customer-facing AI chat, per-tenant branding, or self-hosting.
• Not ideal for: teams that need a published price, or a short contract before they have proven demand.

Fact card: Power BI and Power BI Embedded

• Pricing (as of October 2026): Pro $14 and PPU $24 per user per month, paid yearly; Embedded A1 $1.0081 per hour; Fabric $0.18 per CU per hour (East US).
• Deployment: Power BI service on Azure; Power BI Report Server on-premises for internal reports.
• Databases and warehouses: Power Query connectors for SQL Server, Snowflake, Google BigQuery, Azure Databricks, PostgreSQL, MySQL, and many more (Power BI data sources); an on-premises data gateway handles private databases.
• Query model: Import, DirectQuery, and Direct Lake on Fabric.
• Security: RLS roles (Viewers only); embed tokens with effective identity; Entra ID for internal users; no Power BI-specific SCIM.
• AI: Copilot on F2 and P1 or higher; for app-owns-data, only the Copilot narrative visual (preview); Q&A retires February 2027.
• Embedding: JavaScript client, React wrapper, REST APIs, service principal profiles.
• Best for: teams already on Microsoft 365 and Azure that want capacity pricing they can calculate and pause.
• Not ideal for: Mac-based product teams, customer-facing AI chat, or deployments outside Azure.

What if neither Sisense nor Power BI fits?

Teams that rule out both usually want a published price, a lighter SDK, or AI-first embedding. The Sisense alternatives comparison covers eight embedded platforms in detail, and the Power BI alternatives comparison covers internal BI replacements. In short: Luzmo and Databrain publish embedded pricing, Embeddable and GoodData suit engineering-led products, and Metabase is the low-cost or open-source option.

Basedash is another option, if your customers mainly need to ask questions and you would rather not build chart components.

Fact card: Basedash

• Pricing (as of October 2026): Startup is $1,000 per month plus AI usage for up to 25 users; Enterprise is custom. Embedding is Enterprise only (pricing). 14-day free trial, no credit card.
• Deployment: cloud, or self-hosted with Docker Compose or Kubernetes on Enterprise.
• Databases and warehouses: direct connections to PostgreSQL, MySQL, SQL Server, Oracle, Snowflake, BigQuery, Redshift, Databricks, ClickHouse, and others, plus a managed warehouse for SaaS sources.
• Query model: live queries against your database.
• Security: row-level security through Postgres and Supabase policies only; signed, locked filters on shared dashboards; SSO and SCIM on Enterprise.
• AI: an AI data analyst that answers in chat with tables and charts and builds dashboards.
• Embedding: @basedash/embed React SDK or iframe, with one Basedash organization per customer and short-lived signed tokens (embedding).
• Best for: SaaS teams that want customers to chat with their own data on a Postgres or warehouse backend.
• Not ideal for: products that need a large catalog of hand-tuned chart components, pixel-perfect reports, or RLS on databases other than Postgres. The React SDK is young.

Sisense vs Power BI: which should you choose?

• You run on Azure and Microsoft 365: Power BI Embedded. Entra ID, Fabric capacity, and your existing Power BI reports carry over.
• You need a cost estimate before a sales call: Power BI. A1 at about $736 a month and F2 at about $263 a month are public, and both can be paused.
• Thousands of customers will view dashboards: Power BI capacity pricing doesn’t count end users. Ask Sisense for a quote that states how end users and tenants are counted, and compare both at your expected peak load.
• Your customers should chat with their data inside your product: Sisense today, or Basedash or Luzmo from the alternatives. Power BI documents no embedded chat for app-owns-data.
• Each customer needs its own login URL, SSO, and branding: Sisense self-contained multitenancy.
• You must self-host outside Azure, or on-premises: Sisense on Linux or Kubernetes.
• Your product team builds charts in React code: the Sisense Compose SDK. Power BI embeds visuals designed in Windows-only Desktop.
• Your data is over a billion rows or changes constantly: Sisense Live models, or Power BI DirectQuery or Direct Lake, so neither tool copies the data.

For the architecture behind tenant separation, read how to isolate customer data in embedded dashboards. For the wider market, see the embedded analytics platforms comparison.

Frequently asked questions

Is Sisense or Power BI better for embedded analytics in a SaaS product?

Power BI Embedded is usually better for SaaS companies on Azure that want public, pausable capacity pricing and already build reports in Power BI Desktop. Sisense is usually better when the product needs customer-facing AI chat, per-tenant login and branding, charts composed in React, Angular, or Vue, or self-hosting outside Azure. Both handle multi-tenant row-level security. Ask Sisense for a quote early, because its price is the biggest unknown in the comparison.

Do my customers need Power BI licenses to view embedded reports?

No, not in the “embed for your customers” scenario, which Microsoft also calls app owns data. Your application signs in with a service principal or master user, generates embed tokens, and runs the reports on Power BI Embedded (A SKU) or Fabric (F SKU) capacity. End users never sign in to Power BI. In the “embed for your organization” scenario, each viewer needs a Power BI license, and on F2 through F32 capacity that means Pro or Premium Per User.

How much does Power BI Embedded cost compared to Sisense?

As of October 2026, Power BI Embedded A1 costs $1.0081 per hour in East US, about $736 for a full month. Fabric F2 is about $263 a month pay-as-you-go, and F64 about $8,410, or about $5,003 with a one-year reservation. Sisense publishes no prices; its Self-Serve and Enterprise plans are quoted, and AI on the managed LLM uses paid credits. Compare the two at your expected peak concurrency, because Power BI cost scales with capacity size, not viewer count.

Which has a React SDK for embedding charts, Sisense or Power BI?

Both do. Sisense’s Compose SDK (@sisense/sdk-ui and @sisense/sdk-data) lets developers build charts and dashboards in React code against a Sisense data model, with Angular and Vue packages too. Power BI’s powerbi-client-react wraps the Power BI JavaScript client in a PowerBIEmbed component that displays reports and visuals authored in Power BI Desktop. Pick Sisense if engineers design the charts in code, and Power BI if analysts design them in a visual tool.

Can Sisense or Power BI be self-hosted or run on-premises?

Sisense can be self-hosted on Linux or Kubernetes (EKS, GKE, AKS, or OpenShift) in AWS, Azure, Google Cloud, Oracle Cloud, or your own data center. Power BI’s cloud service runs only on Azure. Power BI Report Server hosts Power BI and paginated reports on-premises for internal users, licensed through Fabric F64-or-larger reservations or SQL Server, but it doesn’t offer the app-owns-data embedding that customer-facing apps use.

Does Power BI Copilot work for external customers in embedded reports?

Only partly. Copilot needs F2 or larger Fabric capacity, or P1 Premium. For app-owns-data embedding, Microsoft documents only the Copilot narrative visual, and it is in preview. It writes summaries of the report but doesn’t give your customers a chat. The older Q&A visual retires in February 2027. Teams that want a customer-facing chat usually look at Sisense’s Assistant or at AI-first embedded tools.

Who are Sisense’s main competitors for embedding analytics into a product?

The vendors most often compared with Sisense for embedded analytics are Power BI Embedded, Luzmo, GoodData, Embeddable, Databrain, ThoughtSpot Embedded, Sigma, Metabase, and Basedash. Luzmo and Databrain publish starting prices. Embeddable and GoodData target engineering-led, SDK-first products. ThoughtSpot and Sigma query cloud warehouses live at enterprise scale. Metabase is open source and low-cost. Basedash embeds an AI data analyst on your own database.