Best Reveal BI Alternatives for Embedded Analytics in 2027

The best Reveal BI alternatives for embedded analytics in 2027 fall into two groups. Embedded analytics platforms with customer self-service, led by Draxlr, Luzmo and Qrvey, take the build work off your developers. Developer-focused SDKs and toolkits such as Bold BI, Sisense, Embeddable and GoodData keep that work in code, much like Reveal. Across both groups, the tools differ on the things that push teams away from Reveal in the first place. Those are how much code your developers write to get analytics live, where tenant isolation is configured, how AI is paid for, and whether you can see a price before a sales call.

Draxlr gives each of your customers a complete analytics workspace inside your app, with the dashboards you share, their own dashboards and saved queries, a no-code query builder and a built-in AI assistant. Row-level security is a permission you set up in Draxlr, with no isolation code on your server, and your backend makes one API call to embed it. There is no analytics server to add to your stack and no LLM account to connect, because Draxlr runs the platform and the AI comes with the plan. Teams that need analytics inside their own network can self-host Draxlr with Docker on the Enterprise plan. Embedding starts at $75/month flat with unlimited customer viewers, and row-level security and full app embedding start at $250/month.

This guide compares the tools on integration work, what customers can build, tenant isolation, how AI is paid for and published pricing. Vendor details were checked against each vendor's own website, pricing page and documentation on 3 and 4 November 2026.

Why do teams look for Reveal BI alternatives?

Reveal, made by Infragistics, is an embedded analytics platform that your developers build into your product with its SDKs. They install Reveal's server library in your .NET, Node.js or Java backend, and add its JavaScript library to your frontend to show dashboards and let customers edit them. It works with React, Angular, Vue, Blazor and Windows Forms apps, connects to more than 30 data sources, embeds natively without iframes, and is sold at one flat rate with unlimited users and no extra cost as your customer base grows (Reveal pricing).

That gives developers a lot of control, and it also leaves much of the build to them. These are the points teams weigh when they compare Reveal with other tools.

• Your developers build the integration. Dashboards load through the Reveal server in your backend. By default the SDK saves them as .rdash files in a folder on that server, and storing them anywhere else means writing your own dashboard provider and save logic. Reveal's docs also say the SDK "does not provide a Save As implementation", so letting a customer save a copy of a dashboard under a new name is code your team writes (Reveal saving docs).
• Your team writes the tenant rules. Reveal enforces tenant isolation as each query runs, but the rules come from your server code. A user context provider passes who is signed in, an object filter hides the data sources and tables a user shouldn't see, and data source callbacks point each tenant at its own database or fill in query parameters. Your team writes, tests and maintains that code (Reveal user context docs).
• AI runs on an LLM account you bring. Reveal doesn't host the AI model itself (Reveal AI). You add a provider package for OpenAI, Azure OpenAI, Anthropic or Google Gemini, or point it at any OpenAI-compatible endpoint, and that provider bills you for the usage. Reveal's AI server packages for Node.js and Java are still marked as preview (Reveal AI requirements).
• Customers can't write or save their own queries. They can edit dashboards, add visualizations and calculated fields, and, if you set up Reveal AI, ask questions in plain English, all on the data sources your code exposes. Custom SQL is set in your server code, and Reveal's docs describe no way for a customer to write a query or keep one as their own (Reveal custom queries docs).
• No scheduled reports or alerts. Customers can export dashboards to PDF, PowerPoint, Excel, CSV and images, and your code can export Excel, PDF and PowerPoint files on the server. Neither Reveal's website nor its docs mention scheduled email reports or data alerts, so any schedule is something your team builds and runs.
• Pricing is quote-only. Reveal doesn't publish prices, so a budget starts with a quote request. Your LLM provider bills AI usage separately, and if you host Reveal yourself, you also pay for the servers it runs on.

What should you look for in a Reveal BI alternative?

• How much code it takes. An SDK you wire into your backend, a platform you configure and embed with a snippet, or dashboards your developers write as code. Each one moves a different amount of work onto your team.
• What customers can do. Viewing dashboards, editing them, building new ones, saving their own queries and asking an AI are different ceilings. Match the ceiling to what your customers already ask your support team for.
• Where the tenant rule lives. In code on your server, in a signed embed token, in a prepared dataset or in a permission configured in the product. If customers can build their own queries, the rule has to hold on those as well as on the dashboards you ship.
• How AI is paid for. Credits included in the plan, credits bought separately, or your own LLM provider account billed directly.
• Where it runs. Vendor-hosted, self-hosted, or both. If data has to stay in your network, ask what self-hosting involves, since a few Docker containers and a Kubernetes cluster are very different jobs.
• Whether the price is published. Flat, per user, per application or usage-based, and whether you can see it before a sales call.

What are the best Reveal BI alternatives in 2027?

Draxlr publishes this guide. Details for the other tools come from each vendor's own website, pricing page and documentation, checked on 3 and 4 November 2026.

Best embedded analytics platforms with customer self-service

These platforms give your customers self-service analytics and handle tenant isolation for you, so your team configure and embed analytics with no build project. They are the strongest fit for teams that chose Reveal for customer-facing analytics and want less code to maintain.

1. Draxlr

Best for teams that want every customer to get a full analytics workspace, without an analytics server in their own stack.

Draxlr is an embedded analytics platform for SQL databases that puts the whole analytics experience inside your product, from a single dashboard to the full Draxlr app. Where Reveal hands your developers an SDK to assemble, Draxlr comes ready to use. Row-level security is a permission you set in the product, the AI assistant is built in, and every dashboard and saved query is kept in Draxlr, so your team writes no code to save or load them.

• Customer self-service. Full app embedding gives each customer their own analytics workspace inside your product. A customer who just wants the numbers opens the dashboards you share. One who needs a new report builds it with the no-code query builder or asks the AI assistant, then saves it as their own query and turns it into a dashboard. Customers with an analyst on staff can also use the SQL editor, and you choose which of those tools each embed exposes. When a page only needs a fixed view, you can embed a single white-labeled dashboard with filters and drill-downs instead.
• Multi-tenancy. Row-level security keeps each customer to their own data, and you set it up once in Draxlr. You choose which tables each group of customers can see and which rows belong to them, and that applies to every dashboard, saved query and AI answer, whether you embed one dashboard or the full app. There is no access logic to write in your own code.
• Hosting. Draxlr runs the platform and handles every update, so there is no analytics server to add to your stack. If data has to stay inside your own network, you can run it on a dedicated server in the region you choose, or self-host it with Docker on your own cloud or servers.
• AI. Customers ask a question in plain English, and Draxlr AI answers it from their data, shows the query it ran and explains the result. Each customer only gets answers from their own data, and they can open and adjust the query behind any answer. There is no LLM account for you to connect. Your own team can also ask Draxlr questions from Claude, ChatGPT or Cursor and add the answers to dashboards your customers see (Draxlr MCP server).
• Pricing. Prices are published and flat, with unlimited customer viewers. Premium is $75/month for white-labeled dashboard embedding. Power is $250/month and adds row-level security and full app embedding. Enterprise starts at $500/month and adds single sign-on, audit logs and self-hosting. You can pay monthly or yearly, and the 7-day free trial gives you the Power plan with no credit card (embedded analytics pricing).
• Watch out for. Draxlr works with 14 SQL databases and data warehouses, plus Airtable and Excel or CSV uploads. Data in MongoDB, Elasticsearch or web APIs has to be moved into a SQL database first, while Reveal connects to those directly. Dashboards export to PDF and Excel but not PowerPoint, and Draxlr can't be embedded in Windows Forms desktop apps. Row-level security and full app embedding need the Power plan. AI usage comes from one monthly allowance shared by all your customers, 300 credits on Power with 200 more for $10. Credits only count AI questions, so customers can keep using the query builder and SQL editor after the allowance runs out.

2. Luzmo

Best for teams that want a hosted embedded dashboard editor with packages for every major frontend framework.

Luzmo runs as managed SaaS and embeds dashboards as a web component, with packages for React, Vue, Angular and React Native. Like Reveal, it embeds natively, but your backend only generates an embed token and hosts no analytics server.

• Customer self-service. Customers create, edit and clone dashboards in an embedded drag-and-drop editor, upload and join their own data, and add fields of their own. SQL for datasets stays on your team's side, in Luzmo's dataset and query panels.
• Multi-tenancy. Parameter filters are set on the dataset and overridden per user in the embed token, so a customer can't remove them in the editor. Connection overrides can point each tenant at its own database, and Luzmo says the same token scope applies to AI answers (Luzmo multi-tenant docs).
• Hosting. Luzmo hosts it. Private infrastructure, a custom SLA and source-code escrow are a quote-only enterprise deployment.
• AI. Luzmo IQ answers plain-language questions with charts inside your product, and an MCP server and agent API take the same answers into Claude, ChatGPT and your own bots. The licence includes 500 AI conversations a month.
• Pricing. One plan, "Embedded Everywhere", from €1,995/month billed annually. Usage is billed on top, with 500 AI conversations and 100 million Warp rows a month included and some contracts scaling on monthly active users instead. The free trial runs 10 days (Luzmo pricing).
• Watch out for. If you chose Reveal to keep analytics on your own servers, Luzmo offers that only as a custom enterprise deployment. Customers build on datasets your team prepares and don't get a SQL editor or saved queries of their own, which is the sharpest difference in a head-to-head with Draxlr.

3. Qrvey

Best for SaaS vendors that want unlimited tenants on a flat or perpetual licence inside their own cloud.

Qrvey keeps analytics in your own infrastructure, like a self-hosted Reveal, but it runs as a whole platform in your cloud account instead of an SDK inside your app. It installs with Terraform into AWS or Azure and embeds as web-component widgets, authenticated with a security token your backend requests from Qrvey's API (Qrvey quickstart).

• Customer self-service. Customers build dashboards with a drag-and-drop chart builder, custom formulas and custom datasets, design pixel-perfect reports and set up alerts and triggers in a no-code workflow builder.
• Multi-tenancy. Qrvey describes security at the row, column, object, asset and feature level, and record-level security is enforced through the token your backend generates.
• Hosting. On AWS that means an EKS cluster, a PostgreSQL database and a search cluster in your account, with at least 56 vCPUs of EC2 quota, and Qrvey warns that an upgrade can take up to two hours of downtime (Qrvey AWS deployment docs). Its Managed Infrastructure package puts Qrvey's DevOps team in charge of monitoring, patches and upgrades inside your account.
• AI. Sidekick and Qrvey's AI agents run through its MCP server on an LLM provider you connect, such as OpenAI, Azure OpenAI or Claude in Amazon Bedrock, so that provider bills the usage, much as it does with Reveal (Qrvey AI docs).
• Pricing. Not published. Qrvey Pro and Qrvey Ultra are flat-rate with unlimited tenants, users and dashboards, both are available as a perpetual licence, and a quote arrives by email within 24 hours (Qrvey pricing).
• Watch out for. Pro queries six SQL sources live through Live Connect, and loading MongoDB, S3 files or API data into Qrvey's own engine needs Ultra. Running that stack in your account is the trade-off most Qrvey alternatives evaluations turn on.

Best developer-focused SDKs and toolkits

These tools keep more of the work in your developers' hands, much like Reveal. They suit teams that want to keep coding the analytics experience but on a different SDK, pricing model or deployment.

4. Bold BI

Best for developer teams that want an embedding SDK with published per-user or per-application pricing.

Bold BI, from Syncfusion, is the closest match to Reveal on this list for teams that like working with an SDK. Its JavaScript SDK installs from npm and renders dashboards inside your app's own DOM, with React, Angular, Vue, .NET and Blazor named as supported frameworks, and an iframe is available when you want less code (Bold BI embedded analytics).

• Customer self-service. Dashboards are built in the Dashboard Designer, where AI Copilot turns a plain-English request into a chart and Prompt to Dashboard builds a six-widget starter dashboard from one prompt. When customers need more than one dashboard, Full Server Embedding puts the whole Bold BI platform inside an iframe in your app.
• Multi-tenancy. Row-level security is enforced at query time through JWT claims, in up to three layers of isolation code, custom attributes and user-based filters. One instance can serve many isolated tenants, each with its own database, on Managed Private Cloud and On-Premises. Bold BI states that its Cloud Edition does not support multi-tenancy.
• Hosting. Cloud Edition is hosted by Bold BI, Managed Private Cloud is operated by Bold BI in a region you choose, and On-Premises runs on your own Windows, Linux, Docker or Kubernetes servers, including air-gapped ones.
• AI. AI features use credits, sold at $40 per 1,000. On On-Premises you can use your own OpenAI, Azure OpenAI or Anthropic key instead, while Cloud Edition uses Bold BI's own AI service.
• Pricing. Published. On-Premises starts at $499/month for 100 users plus $3 for each additional user, Cloud Edition at $999/month for 100 users plus $5 per user, and per-application pricing for unlimited users is $1,999/month on your own servers. Managed Private Cloud is quoted, every edition includes white-labeling, row-level security and scheduled reports, and the free trial runs 30 days with no credit card (Bold BI pricing).
• Watch out for. Cloud Edition doesn't support Bold BI's multi-tenant setup, where each tenant gets an isolated database, so that needs On-Premises or the quote-only Managed Private Cloud, although row-level security works on every edition. Per-user pricing grows with every customer user unless you move to per-application licensing on your own servers, and AI credits are bought separately from the licence.

5. Sisense

Best for enterprises that need SDK embedding with on-premise deployment.

Sisense embeds with iframes or the Compose SDK, on data models that either import your data or query your warehouse live.

• Customer self-service. Customers explore dashboards and build widgets, depending on the roles you give them, and Self-Serve includes natural-language queries, auto-narratives and an assistant your customers can use.
• Multi-tenancy. Data security rules give row-level access, and Enterprise adds a native multi-tenant architecture, column-level security and an SSO Router.
• Hosting. Sisense cloud on Self-Serve. Enterprise adds your own cloud on AWS, Azure or GCP, and on-premise deployment.
• AI. Enterprise lets you bring your own LLM alongside the Sisense Intelligence suite.
• Pricing. Not published. The plans page lists Self-Serve, which has a free trial, and Enterprise, which is built to your specification (Sisense plans).
• Watch out for. Native multitenancy, full white-labeling and on-premise deployment all sit on the quote-only Enterprise plan.

6. Embeddable

Best for developer-led teams that want dashboards as code in their own repository.

Embeddable suits teams that liked Reveal's developer control and want it in their own repository. Charts are React components, data models are written in Cube, and dashboards can be built in a no-code builder or defined as files in your codebase. They embed as a web component for React, Vue, Angular or plain HTML, authorized by a short-lived token your server mints (Embeddable embedding docs).

• Customer self-service. Custom Canvas lets customers build and customise their own dashboards from templates you define.
• Multi-tenancy. Row-level security is enforced server-side from the security context in each token, through security filters, SQL-based rules or access policies.
• Hosting. Embeddable runs the platform on AWS in a US or EU region, and queries run live against your database without copying it. If you need more control, you can run its Cube data layer in your own environment (Embeddable security).
• AI. Your team can scaffold dashboards as code from a prompt with Embeddable's Claude skill. For customers, the docs list an AI chatbot and chat endpoint as on the way.
• Pricing. Not published. Plans are a flat monthly subscription with no usage-based pricing, quoted for your project, and evaluation starts with a supported proof-of-concept phase (Embeddable pricing).
• Watch out for. Modeling in Cube and building components takes frontend and data engineering time, so the code Reveal asked for moves into components and models instead of going away.

7. GoodData

Best for multi-tenant products that need governed metrics across many customer workspaces.

GoodData is an API-first analytics platform that gives each customer a workspace of their own, with a React SDK and a Python SDK for your developers.

• Customer self-service. Customers get unlimited self-service reports and dashboards inside their own workspace.
• Multi-tenancy. Multitenancy is built in with hierarchical workspaces, and data filters limit what each workspace and user can see.
• Hosting. GoodData's cloud, with self-hosted deployment as an on-demand Enterprise option.
• AI. An AI assistant, an agent builder and an MCP server are part of the platform.
• Pricing. Not published. Professional is a platform fee plus a charge per workspace, with unlimited users and data, and Enterprise adds governance and self-hosting (GoodData pricing).
• Watch out for. The bill rises with every tenant workspace you add, and your team builds a semantic data model before customers see a chart.

Explo still shows up on Reveal BI shortlists as a developer-friendly embedding option. Omni acquired it on 22 October 2025 and said it would spend the following 12 months moving Explo customers onto Omni (Omni announcement), so a new project on Explo means planning a second migration.

Which Reveal BI alternative is right for you?

What is the best Reveal BI alternative?

For most teams moving off Reveal, the best alternative is Draxlr. Your customers get more than a dashboard editor. Each one opens a complete analytics workspace inside your product, builds reports with a no-code query builder or the AI assistant, saves them as their own queries and dashboards, and keeps receiving scheduled reports and alerts without anyone writing code for it. Your developers stop maintaining a Reveal server, provider classes and tenant rules in your backend, because row-level security is a permission configured in Draxlr and the embed is one API call plus a snippet, the main point most Draxlr vs Reveal BI evaluations turn on. If the data must stay inside your network, the Enterprise plan self-hosts with Docker. Pricing is published and flat with unlimited customer viewers, from $75/month for white-labeled dashboard embedding and $250/month for row-level security and full app embedding.

Pick another tool when one requirement outweighs the rest. Among the embedded platforms, Luzmo suits teams that want a hosted dashboard editor with packages for every major framework, and Qrvey fits unlimited tenants on a perpetual licence in your own cloud. Among the developer-focused tools, Bold BI suits developers who want an SDK with a published self-hosted price, Sisense fits enterprise SDK embedding with on-premise deployment, Embeddable fits dashboards as code and GoodData fits governed metrics across many workspaces.

Whichever you shortlist, test it against your real database, your tenant model and the number of customers you expect before you sign.

FAQs

1. What is Reveal BI?

Reveal BI, sold by Infragistics as Reveal, is an embedded analytics platform that developers build into a product with its SDKs. They install Reveal's server library in a .NET, Node.js or Java backend, show dashboards with its JavaScript library, and write providers that handle tenant context, data source credentials and dashboard storage. It connects to more than 30 data sources, adds AI through an extension that runs on your own LLM provider, and is sold at one flat rate with unlimited users.

2. How much does Reveal BI cost?

Reveal doesn't publish prices. Its pricing page describes one flat rate with unlimited users, no extra embed cost as your customer base grows and every data connector included, and pricing starts with a quote request. A 30-day trial of the SDK is available to download. Budget separately for the LLM provider Reveal AI runs on and, if you host Reveal yourself, for the servers it runs on.

3. Who are Reveal BI's main competitors?

Reveal's competitors fall into two groups. Embedded analytics platforms include Draxlr, Luzmo and Qrvey, and developer-focused SDKs and toolkits include Bold BI, Sisense, Embeddable and GoodData. Of these, Draxlr is the pick when you want customers to get a full analytics workspace without an SDK in your backend, because it embeds with one API call and a snippet and gives each customer saved queries, a no-code query builder and a built-in AI assistant.

4. Which Reveal BI alternatives don't need code on your server?

Draxlr and Luzmo both run as hosted platforms, so your backend only requests an embed URL or token and nothing analytics-related runs in your stack. Bold BI's Cloud Edition and Sisense's cloud plans are hosted too. Qrvey and Bold BI On-Premises run in your own infrastructure as a separate platform, and Embeddable asks your developers to write components and data models as code.

5. How is AI paid for in Reveal and its alternatives?

Reveal AI runs on an LLM provider you connect, such as OpenAI, Azure OpenAI, Anthropic or Google Gemini, so that provider bills your own account, and Qrvey works the same way. Bold BI sells AI credits at $40 per 1,000, or lets you bring your own key on its On-Premises edition. Luzmo includes 500 AI conversations a month with usage above that billed on top, and Draxlr includes AI credits in the plan, 300 a month on Power with 200 more for $10. On Draxlr, credits cover only AI messages, so customers keep using the query builder and SQL editor once the month's credits are spent.

6. Which Reveal BI alternatives handle multi-tenant row-level security?

Every embedded platform and SDK in this guide isolates tenant data, in different ways. Draxlr makes row-level security a permission configured in the product, applied from the RLS group and attribute values your backend sends with the embed URL request, on the Power plan. Luzmo sets parameter filters on the dataset and overrides them per user in the embed token, Bold BI enforces row-level security through JWT claims, and Embeddable reads a security context passed in its tokens. Qrvey carries record-level security in a token your backend generates, Sisense uses data security rules, and GoodData combines a workspace per tenant with data filters. In Reveal itself, the tenant rules are code you write in the server's user context and data source providers.

7. Is there a self-hosted Reveal BI alternative?

Yes. Draxlr's Enterprise plan runs self-hosted with Docker in your VPC or on-premise, or on a dedicated server in the region you choose. Bold BI On-Premises runs on your own Windows, Linux, Docker or Kubernetes servers, including air-gapped ones, Qrvey installs into your own AWS or Azure account, and Sisense offers on-premise deployment on Enterprise.

8. How hard is it to move from Reveal BI to another tool?

Reveal saves dashboards as .rdash files, its own ZIP-based format, so plan to rebuild your most-used dashboards in the new tool. Moving to Draxlr mostly means deleting code. You connect the SQL databases your Reveal data source provider points at, rebuild dashboards with the query builder or the AI assistant, turn the tenant rules in your Reveal server code into a row-level security permission, and replace RevealView in your frontend with Draxlr's HTML snippet or its React or Vue package. Once the last customer has moved, the Reveal packages and providers can come out of your backend.