10 Best Embedded Analytics Tools (2026 Pricing)

Customers now expect dashboards inside the software they already pay for. They don't want a CSV export and a spreadsheet. In 2026, Fortune Business Insights valued the global embedded analytics market at $26.88 billion, and it projects 15.68% annual growth through 2034 (Embedded Analytics Market report).

The hard part is picking from dozens of embedded analytics tools. Most of the big names were built as internal BI platforms. Embedding them usually means showing customers dashboards you built. Letting customers ask their own questions, safely, is a much harder problem, and few tools solve it.

This guide compares ten embedded analytics tools, from SQL-first products built for SaaS teams to the big cloud BI platforms. For each one you'll see how embedding works, what your customers can do inside the embed, what it costs and who it suits.

Key Takeaways

• Draxlr lets customers go beyond viewing dashboards. Inside your product they can write raw SQL and ask an AI assistant questions, and row-level security applies to every query and every AI answer. Few embedded tools let external users write their own SQL with row-level rules still enforced.
• Draxlr is built to extend. Embed with HTML, React or Vue, or build your own features on top with API endpoints, a backend embed API and an MCP server.
• Six of the ten tools here don't publish embedded pricing. Vendr's buyer data puts median contracts for Domo, Sisense, Sigma and ThoughtSpot at $50,000–$100,000 a year (Vendr, February 2026).
• Test what customers can actually do in the embed, and whether your data rules still hold when they do it, before you shortlist anything.

Quick Comparison: Embedded Analytics Tools at a Glance

The table below sums up all ten tools. "Starting cost" uses the vendor's published price where one exists. Where it doesn't, it uses the median annual contract from Vendr's purchase data.

What Is Embedded Analytics?

Embedded analytics puts charts, dashboards and reports directly inside another application. That might be your SaaS product, a customer portal or an internal tool. Your users see their data in context, and they never log in to a separate BI tool.

A good embedded setup handles three jobs:

• Presentation. Dashboards match your product's look, with no vendor logo getting in the way.
• Isolation. Each customer sees only their own rows. That's usually done with a tenant filter or row-level security.
• Authentication. Your backend vouches for the logged-in user, often with a signed token, so viewers don't need separate accounts.

Anything short of all three means building the missing piece yourself.

1. Draxlr: Best Overall for SaaS Teams

Most embedded analytics tools let your customers look at dashboards you built. Draxlr also lets them ask their own questions. With full app embedding, customers can write raw SQL, ask an AI assistant in plain English or use a no-code builder, all inside your product. Row-level security applies to every one of those queries, so each customer only ever sees their own data. You connect a SQL database, build dashboards and add the embed to your app (Draxlr docs).

Why teams choose it:

• Raw SQL in the embed, with row-level security. Your customers get a SQL editor inside your product. Draxlr applies their row-level rules to every statement they write. Queries that touch a table they aren't allowed to use return a permission error instead of data (Draxlr docs). Few embedded tools give external users SQL access at all.
• AI in the embed, under the same rules. Customers can ask questions in plain English and get charts back. The AI assistant goes through the same row-level security as everything else, so it can't reveal another customer's rows.
• Full app embedding. Go beyond a single dashboard and put a complete analytics workspace inside your product. Your customers get the dashboards you share, plus their own saved queries and dashboards. You choose which tools they get: AI, SQL, the visual builder or any mix.
• Row-level security you define once. Decide which tables each group can query and which rows it can see. Draxlr applies these rules to every dashboard, saved query, SQL statement and AI answer, for your team and your customers alike.
• Build custom solutions on top. Turn any saved query into an API endpoint that returns JSON (Draxlr docs). Generate embed URLs from your own backend, and connect AI agents through the MCP server. You can build your own product features on Draxlr's query layer, not just drop in its UI.
• Flexible embedding. Embed with an iframe, the ReactJS SDK, the VueJS SDK or backend APIs. For secure embeds, your backend calls Draxlr's API with filters and gets back a JWT to inject into the page (Draxlr docs).
• Simple multi-tenancy. Add a hidden filter such as AccountId and pass the logged-in customer's value. Each tenant then sees only their own data.
• White label, matched to your product. Embeds carry no Draxlr branding. Match your brand colors, hide the header and choose whether viewers can filter, drill down or export.
• Access control. A domain allowlist stops other sites from loading your embed code.
• Wide database support. It connects to PostgreSQL, MySQL, MariaDB, SQL Server, Supabase, PlanetScale, CockroachDB, YugabyteDB, ClickHouse, Redshift, BigQuery, Snowflake and Databricks.
• Enterprise ready. Self-hosting, SSO and audit logs are available on the Enterprise plan.

Pricing: Premium is $75/month for 2 databases and 10 users, with dashboard embedding and white label embeds. Power is $250/month for 5 databases and 30 users, and adds full app embedding and row level security. Enterprise starts at $500/month and adds self hosting, SSO and audit logs. All plans include unlimited external viewers. You also get a 7-day free trial of Power with no credit card.

Watch out for: Draxlr is built for SQL databases and warehouses. If your data sits in spreadsheets or SaaS APIs, you'll need to load it into a database first.

Best for: Product teams, from startups to enterprises, that want to give customers more than read-only dashboards: their own SQL, AI answers and dashboards, with row-level security on all of it.

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2. Tableau: Best for Salesforce-Centric Enterprises

Tableau is the best-known name in data visualization. Its embedded offering is aimed at large companies that already run Tableau internally. Salesforce doesn't publish an embedded price. Instead, it offers usage-based licensing: external Usage Viewers are billed per "analytical impression" while Creators and Explorers stay per user (Tableau Help).

Why teams choose it:

• It has the deepest visualization toolkit of any tool here, plus a huge community.
• The Embedding API v3 and Connected Apps give you single sign-on and control over interactions.
• Usage-based licensing can make more sense than per-seat Viewer licenses when viewers log in rarely.

Pricing: Embedded is sales-led. You'll also need Creator licenses for the people building dashboards and a Tableau Cloud or Server deployment.

Watch out for: The total cost is hard to forecast before you sign. Styling embeds so they don't look like Tableau also takes real effort.

Best for: Enterprises with Tableau skills in-house and budget for a multi-year contract.

3. Microsoft Power BI Embedded: Best for Azure Shops

Power BI Embedded charges for dedicated capacity instead of per viewer. On Microsoft's retail price list, the smallest A1 node costs $1.0081 per hour in East US. That's about $736 a month if it runs all the time. An A6 node costs $32.25 per hour (Azure Retail Prices API, retrieved September 2026).

Why teams choose it:

• With the "app owns data" model, your customers don't need Power BI licenses.
• Row-level security is mature and well documented.
• Nodes can be paused, which helps if usage follows business hours.

Pricing: You pay per capacity node, billed hourly. Anyone publishing reports needs a Power BI Pro or Premium Per User license, but your customers need no license in the app-owns-data model (Microsoft Learn).

Watch out for: Choosing a node size is guesswork until real traffic arrives. An undersized node slows every customer's dashboards at once.

Best for: Products already hosted on Azure, with developers who know the Microsoft stack.

4. Looker: Best for a Governed Semantic Layer

Looker, part of Google Cloud, sells a dedicated Embed edition. It adds signed embedding and custom themes, plus 500,000 query-related API calls and 100,000 admin API calls per month (Google Cloud docs). Every edition is sold on an annual contract, with no public price list.

Why teams choose it:

• LookML defines each metric once, so every customer sees the same logic.
• Queries run directly on your warehouse, with no extract to keep in sync.
• It integrates tightly with BigQuery and the rest of Google Cloud.

Pricing: You'll need a custom quote through Google Cloud sales. Plan for a separate non-production instance too, since Google recommends one for staging.

Watch out for: LookML has a real learning curve. The API call caps also matter once your embedded traffic grows.

Best for: Data teams with modeling skills that are already committed to Google Cloud.

5. Amazon QuickSight: Best for AWS-Native Products

Amazon QuickSight, now branded Amazon Quick Sight, is the only tool here that publishes session-based embedded pricing. A monthly plan includes 500 reader sessions for $250 and charges $0.50 for each extra session. Annual plans start at $20,000 for 50,000 sessions, and each session lasts 30 minutes (AWS pricing).

Why teams choose it:

• Anonymous embedding means you don't have to create a user for every viewer.
• It connects natively to Redshift, Athena, S3 and RDS.
• Pay-per-session pricing suits products with occasional, bursty usage.

Pricing: Authors cost $24/user/month and Readers $3/user/month. Reader capacity runs from $250/month up to $258,000/year for 1.6 million sessions.

Watch out for: Customization is more limited than with SDK-first tools. A $250/month account fee also applies if you enable Pro users or Q&A.

Best for: Teams whose data and infrastructure already live in AWS.

6. Sisense: Best for Code-Level Customization

Sisense has served the embedded market for years. Its Compose SDK lets developers build analytics from React, Angular or Vue components instead of dropping in an iframe. Sisense doesn't publish prices. Vendr's data from 126 purchases shows a median annual contract of $56,831 (Vendr).

Why teams choose it:

• The Compose SDK gives front-end developers component-level control.
• It can join data from multiple sources in its own data layer.
• It has a long track record with software vendors that embed analytics.

Pricing: Custom quotes. In Vendr's data, contracts ranged from $18,139 to $178,681 a year.

Watch out for: Implementation often needs professional services, and the total cost climbs with data volume.

Best for: Product teams with front-end engineers who want analytics to feel fully native.

7. ThoughtSpot Embedded: Best for Natural Language Search

ThoughtSpot lets end users type questions in plain English and get charts back. Its Developer plan is free for one year, for up to 10 users and 25M rows. Production embedding runs on a custom-priced Enterprise Embedded plan (ThoughtSpot pricing). According to Vendr, the median buyer pays $100,000 a year.

Why teams choose it:

• Spotter, its AI agent, answers questions in natural language, and LLM tokens aren't billed separately.
• The Visual Embed SDK can embed search, single charts or full Liveboards.
• It queries cloud warehouses such as Snowflake and Databricks live.

Pricing: The Developer plan is free for a year. Enterprise Embedded is custom-priced. Vendr's reported contracts range from $38,640 to $221,653.

Watch out for: ThoughtSpot's Essentials, Pro and Enterprise analytics plans don't include embedding, so internal BI and customer-facing embedding are separate purchases.

Best for: Well-funded products where self-service questions matter more than fixed dashboards.

8. Qlik Cloud Analytics: Best for Exploratory Analysis

Qlik's associative engine lets users click through linked data freely instead of following a fixed drill path. Anonymous (public) access, which customer-facing embeds often need, starts with the Premium plan. Premium costs $2,750 per month, billed annually, with 50 GB of data (Qlik pricing).

Why teams choose it:

• Associative exploration shows related and unrelated values at a glance.
• The qlik-embed web components work with modern front-end frameworks.
• It has strong data integration through the Qlik Talend portfolio.

Pricing: Premium is $33,000 a year. OEM and external-user arrangements are priced separately through sales.

Watch out for: Pricing is tied to data capacity, so costs grow as your data grows. The scripting language also takes time to learn.

Best for: Analytics-heavy products whose users explore data rather than just check KPIs.

9. Domo Everywhere: Best for Existing Domo Customers

Domo Everywhere is Domo's embedded and white-label offering. It shares dashboards externally from the same platform your internal teams use. Domo uses consumption-based credit pricing and doesn't list embedded rates (Domo pricing). Vendr reports a median contract of $50,000 a year across 91 purchases.

Why teams choose it:

• It bundles ETL, data connectors and dashboards in one platform.
• Its broad connector library covers SaaS apps as well as databases.
• It can publish to partners and customers from a single instance.

Pricing: Custom, credit-based consumption pricing. Vendr's reported contracts range from $10,920 to $175,245.

Watch out for: Credit consumption is hard to predict once external users start querying at scale.

Best for: Organizations already standardized on Domo that want to extend it to customers.

10. Sigma: Best for Spreadsheet-Style Analysis on a Warehouse

Sigma gives users a familiar spreadsheet interface on top of Snowflake, Databricks or BigQuery. Sigma doesn't publish pricing. Across 152 purchases, Vendr reports a median contract of $66,540 a year (Vendr).

Why teams choose it:

• Business users already know how to use a spreadsheet.
• Everything runs live on your cloud warehouse, with no extracts.
• With input tables, embedded users can write data back to your warehouse, not just view it.

Pricing: Custom quote. Vendr's buyer data ranges from $17,500 to $147,142 a year, but Vendr notes embedding is only available on the Enterprise tier, where customer-facing contracts often start around $100,000.

Watch out for: Every embedded interaction runs a query on your warehouse, so those compute costs add to the license fee.

Best for: Companies whose data already lives in a modern cloud warehouse.

How Much Does Embedded Analytics Really Cost?

Costs range from under $1,000 to more than $100,000 a year. Draxlr's Premium plan works out to $900 a year. Vendr puts the median ThoughtSpot contract at $100,000 and the median Sigma contract at $66,540. Six of the ten tools here don't publish a price at all.

Read the chart with one caveat: Vendr medians cover whole-platform contracts, not only embedding. Embedded deals can cost more. Vendr notes Sigma's customer-facing embedded contracts often start around $100,000. Even so, the gap is too wide to be a rounding error.

Three pricing models drive most of the difference:

• Per viewer. Every customer login adds cost. That's fine for 20 users and painful for 20,000.
• Capacity or sessions. Power BI and QuickSight bill for compute or sessions. Costs are predictable at steady traffic, but you have to size them.
• Flat plan with unlimited viewers. Draxlr charges by databases and builder seats, so viewer growth doesn't change the bill.

Before any demo, estimate three numbers: monthly active viewers, how often each one opens a dashboard, and how many people will build dashboards.

How to Choose the Right Embedded Analytics Tool

Start with where your data lives and how many people will view dashboards. Then check the rest:

1. Data source. If you run PostgreSQL, MySQL or a warehouse, a SQL-first tool like Draxlr gets you live fastest. If you're deep in Azure, AWS or Google Cloud, their native tools cut integration work.
2. Viewer economics. Project your viewer count 24 months out and price it under each model. Per-viewer pricing punishes growth.
3. Tenant isolation. Confirm how the tool keeps Customer A from seeing Customer B's data: hidden filters, row-level security or signed tokens.
4. Self-serve depth. Decide whether customers will only view dashboards or also ask their own questions. If they need SQL or AI, check that row-level security covers the queries they write, not just the dashboards you built.
5. Room to build. Check for APIs that let you use the tool's data and queries in your own features, not only inside its UI.
6. Look and feel. Check that you can remove vendor branding and match your fonts and colors on the plan you'll actually buy.
7. Time to launch. Ask whether you need professional services. For some enterprise tools, a paid services package is normal.

How We Selected These Tools

We picked ten tools with dedicated embedded offerings, mixing SQL-first products built for SaaS teams with the established platforms buyers most often shortlist. Open-source tools were left out on purpose.

We compared each tool on six points:

• Embedding methods: iframe, SDKs, APIs and secure token support
• Multi-tenant security: how per-customer data isolation works
• Self-serve depth: whether embedded users can query with SQL or AI, and whether security rules follow them
• Published pricing: list prices where available, otherwise Vendr's buyer-reported contract data
• Ecosystem fit: which cloud and data stack each tool assumes
• Customization: theming and white-label options

Pricing was checked against vendor pages, Microsoft's retail price API and Vendr in September 2026. Prices change often, so confirm with each vendor before you buy.

Frequently Asked Questions

What is the best embedded analytics tool in 2026?

For most SaaS teams on a SQL database, Draxlr is the best embedded analytics tool in 2026. Customers can do more than view dashboards: inside your product they can write SQL, ask an AI assistant questions and build their own dashboards, with row-level security applied to every query. It also offers JWT-secured embeds, React and Vue SDKs and APIs to build your own features on. Teams tied to one cloud may prefer Power BI Embedded, Looker or Amazon QuickSight.

How much does embedded analytics cost?

Embedded analytics costs anywhere from about $900 a year to more than $100,000. Draxlr Premium is $75/month. Power BI Embedded's A1 node runs about $736/month, and QuickSight annual capacity starts at $20,000. Vendr reports median contracts of $56,831 for Sisense and $100,000 for ThoughtSpot.

What is the difference between embedded analytics and traditional BI?

Traditional BI is a separate application that internal analysts log in to. Embedded analytics puts dashboards inside your own product, so customers see their data in context without another login. Embedded tools add multi-tenant data isolation, token-based authentication and white-label styling, which standard BI licenses usually don't include.

Can I embed dashboards without paying per viewer?

Yes. Draxlr includes unlimited external viewers on every plan, and embedding starts at $75/month. Power BI Embedded bills per capacity node instead of per user, and Amazon QuickSight bills per 30-minute reader session. Tableau's usage-based licensing charges for Analytical Impressions rather than named Viewer seats.

How do embedded dashboards keep customer data separate?

Most tools use your app's login to work out which customer is viewing, then show only that customer's data. In Draxlr, you tell it which column identifies a customer, such as an account ID, and each customer automatically sees only their own rows. Row level security goes a step further and lets you control exactly which tables and rows each customer can see across dashboards, queries and AI answers. Power BI and Looker offer similar controls.

Can customers write their own SQL in an embedded dashboard?

With Draxlr, yes. Full app embedding includes a SQL editor and an AI assistant, and row-level security applies to every query a customer writes or asks for. A query that touches a table they aren't allowed to use returns a permission error. Many embedded tools only let external users view or lightly edit prebuilt reports. If you need customer SQL elsewhere, ask the vendor whether its row-level rules cover it.

Can I embed a full analytics app instead of just dashboards?

Yes, several tools on this list support it. Draxlr's full app embedding puts a complete analytics workspace inside your product, starting on the Power plan at $250/month. Customers see the dashboards you share and can build their own queries and dashboards with a no code builder, SQL or AI. Row level security keeps each customer inside their own data.

Elsewhere on this list, ThoughtSpot's Visual Embed SDK can embed the full ThoughtSpot app, and Amazon QuickSight can embed its full console for registered users. Looker's signed embedding covers Explores as well as dashboards, and Tableau and Power BI both let embedded users edit reports. These options sit on top of each platform's usual contract, so the costs in the comparison table still apply.