Every SaaS product collects data its customers would love to see. Usage, spend, performance, activity. Sooner or later someone asks for a report, and your team ends up exporting CSVs or building one-off charts that nobody has time to maintain.
Customer-facing analytics tools fix that by putting dashboards and reports inside your product, where each customer sees only their own data. The tricky part is that the tools in this space solve the problem in very different ways. Some hand you finished, white-labeled dashboards. Some make you model your metrics first. Others give your engineers fast APIs and leave the interface to you.
This guide sorts nine tools into those three approaches, so you can pick the approach first and the tool second. If you're specifically comparing embedding options on a SQL database, our roundup of the best embedded analytics tools in 2026 goes deeper on that.
Key takeaways
- Customer-facing analytics tools fall into three groups: dedicated embedded and white-label platforms, SQL-first and semantic layer tools, and developer-first real-time APIs.
- In BARC's Data, BI and Analytics Trend Monitor 2026, BI vendors reported that 65% of their customers already use embedded BI.
- Tenant isolation and pricing at scale separate these tools more than chart types do. Check both before you sign anything.
What are customer-facing analytics tools?
Customer-facing analytics tools let you show dashboards, reports, and metrics to your own customers, inside your product. They differ from internal BI in three ways: the viewers are outside your company, every customer must be limited to their own data, and the interface has to look like part of your product rather than a separate tool.
That combination is harder than it sounds. An internal dashboard can trust every viewer. A customer-facing one has to assume that any viewer might try to see someone else's numbers, and it has to hold up when thousands of customers load it at once.
Embedded analytics is no longer a niche feature. BARC's Data, BI and Analytics Trend Monitor 2026, published in November 2025, says BI vendors surveyed for its BI & Analytics Survey reported that 65% of their customers already use embedded BI. Dresner Advisory Services' 2025 Embedded Business Intelligence Market Study points the same way.
So customer-facing analytics isn't just a way to cut support tickets. For many SaaS products, it's something customers pay for and a reason they stay.
Three ways to build customer-facing analytics
The biggest difference between these tools isn't the chart library. It's how much of the stack you build yourself. Here's how the work splits up in each approach.
Dedicated embedded and white-label platforms give you finished dashboards that you style to match your product and embed with a snippet or SDK. Tenant security comes from a token your backend signs. These are the fastest way to get something live, and they need the least frontend work.
SQL-first and semantic layer tools start from your data model. You write SQL, or define metrics once in a semantic layer such as LookML, a Cube data model, or an Omni model, and every dashboard, API, and AI assistant uses those same definitions. You get consistency and governance, but someone has to build and maintain the model.
Developer-first and real-time API tools treat analytics as part of your codebase. Engineers write queries as versioned SQL endpoints or define components in code, and your own frontend renders the result. You get full control and very low latency at high volume, but you're building the interface yourself.
Which one fits depends on who you have. A two-person product team without a data engineer is a poor match for a semantic layer. A product where analytics is the product probably shouldn't settle for a generic dashboard embed.
What to look for in a customer-facing analytics tool
Six questions sort out most of the differences between these tools.
Does tenant isolation cover every query? It's easy to filter a dashboard you built. It's harder once customers can build their own charts, write SQL, or ask an AI assistant. Look for row-level rules applied on the server to every query, not hidden dashboard filters. Omni's own embedding best practices put it bluntly: "Segmenting data using hidden dashboard filters is not a secure practice."
How does the price grow? Flat pricing, per-user pricing, monthly active users, compute hours, and vCPU hours can all look similar at launch. Model your bill at 10, 100, and 1,000 customers before you commit.
Who builds and maintains the interface? Embedded platforms ship it. Developer-first tools leave it to you. Every new chart in a custom frontend is a small feature build, not a settings change.
Where does the data live? Some tools query your database directly. Others need data copied or streamed into their own engine. Direct queries are simpler to set up. A dedicated engine is faster at very high volume.
How much setup comes before the first dashboard? Connecting a database takes an afternoon. Writing a semantic model or an ingestion pipeline takes weeks.
How far does white labeling go? Removing a logo is not the same as controlling colors, fonts, and layout. Some vendors include it on every plan. Others charge more for it.
Customer-facing analytics tools at a glance
Every detail below comes from each vendor's own docs and pricing pages, which we checked on October 26, 2026.
| Tool | Category | Starting price | Pricing model | Where queries run |
|---|---|---|---|---|
| Draxlr | Embedded & white-label | $75/month ($250/month with row-level security) | Flat, unlimited embed viewers | Your SQL database, directly |
| Luzmo | Embedded & white-label | €1,995/month, billed annually | Platform fee plus usage | Your database, directly, or an optional sync |
| Qrvey | Embedded & white-label | Not published | Flat rate, unlimited tenants and users | Your database (Pro) or Qrvey's engine (Ultra) |
| Metabase | SQL-first & semantic | Free for guest embeds, $575/month for SSO embeds | 10 users included, then $12/user/month | Your database, directly |
| Omni | SQL-first & semantic | Not published | Sales quote | Your database or warehouse, via Omni's model |
| Cube | SQL-first & semantic | Free tier, embedding on Premium ($80/developer) | Seats for your team, compute for embeds | Your database or warehouse, via Cube's model |
| Tinybird | Developer-first & real-time | Free tier, Developer from $25/month | Plan plus vCPU and storage usage | Tinybird's managed ClickHouse |
| Embeddable | Developer-first & real-time | Not published | Flat monthly subscription | Your database, directly |
| StarTree | Developer-first & real-time | $0.21 per production vCPU hour | Usage-based | Managed Apache Pinot |
Dedicated embedded & white-label platforms
These tools exist to put analytics inside someone else's product. White labeling, multi-tenant security, and embed SDKs are the core product, not add-ons.
1. Draxlr
Draxlr connects straight to your SQL database and lets you embed white-labeled dashboards in your product, or a full analytics workspace for each customer. There's no warehouse or data pipeline to set up first. It supports PostgreSQL, MySQL, SQL Server, MariaDB, Supabase, BigQuery, Snowflake, ClickHouse, Redshift, and more.
How you embed it
Draxlr generates embed code for HTML, React, or Vue. For a customer-facing embed, your backend calls the Generate Embed URL API with your API key and secret, plus an rlsGroup and the customer's attributes, such as accountId: 42. Draxlr then "applies the group's rules with those attribute values to every dashboard element." You can also lock embeds to a list of allowed domains, hide filters, set colors, and turn exports on or off.
If customers need more than a fixed dashboard, Full App Embed gives each one a workspace with a query builder, a SQL editor, an AI assistant, and their own saved dashboards. The same row-level rules apply to all of it.
Pricing
According to Draxlr's pricing page, dashboard embedding with white labeling starts on the Premium plan at $75 per month. Row-level security and Full App Embedding start on the Power plan at $250 per month. Embed viewers and Full App Embed customers "don't count as users," and they're unlimited on every plan, so the bill stays the same at 10 customers or 10,000. Every account starts with a 7-day trial of the Power plan, with no credit card required.
Worth knowing
- For a true multi-tenant embed, plan on the Power plan. Without an
rlsGroup, the embed shows everything the dashboard's queries return.
Where it fits
SaaS teams on a SQL database who want white-labeled, customer-facing dashboards live in days, at a flat price that doesn't grow with their customer count.
Connect your Database2. Luzmo
Luzmo is one of the few platforms built only for embedded analytics. It ships dashboard components for web, React, Angular, Vue, and React Native, plus an embedded dashboard editor that lets your customers build and change their own dashboards.
How you embed it
Your server requests an embed token and adds parameter_overrides to it, so each customer's filters are set before the dashboard loads. Luzmo's multi-tenant guide recommends that "you should set up the embed filter on the dataset level," which keeps customers from removing it in the editor. For a separate database per customer, account_overrides switches the connection per token. By default, queries go straight to your database in real time. Luzmo's optional Warp feature syncs a copy of the data into Luzmo for speed.
Pricing
Luzmo now has one public plan, Embedded Everywhere, starting at €1,995 per month, billed annually. White labeling is included, along with 500 AI conversations per month. Pricing scales with usage, and some contracts scale on monthly active users. The pricing page is direct about it: "There is no smaller tier."
Worth knowing
The entry price rules Luzmo out for many early-stage teams. The editor is also drag-and-drop rather than SQL, which suits business users but frustrates analysts who want to write their own queries.
Where it fits
Funded SaaS teams whose customers are business users who want to build their own dashboards without touching SQL.
3. Qrvey
Qrvey is built for multi-tenant SaaS products and deploys into your own cloud account, so the data stays in your own environment. It's sold in two editions. Pro connects to the data engine you already have. Ultra adds Qrvey's own data engine and transformation layer.
How you embed it
Qrvey's widgets are web components that "work with any modern web framework or plain HTML/JavaScript," including a dashboard builder customers can use themselves. For tenant isolation, "Record-Level Security is implemented as a filter that is embedded within the authentication/authorization token," according to Qrvey's security docs. With Live Connect, Qrvey queries Snowflake, Redshift, Postgres, Databricks, MySQL 8+, or SQL Server without storing the data.
Pricing
There are no public prices. Qrvey's pricing page promises "Unlimited tenants, users, and dashboards under a single flat rate," and says you'll get a quote within 24 hours of filling in a form. Perpetual licensing is also available for both editions.
Worth knowing
On Live Connect, Qrvey's docs say "transformations, calculated fields can be limited or unavailable." Managed datasets, which copy data into Qrvey's engine, are Ultra-only. Running in your own cloud also means your team owns that deployment.
Where it fits
Larger SaaS companies with many tenants, strict data residency requirements, and the appetite for a sales-led purchase.
SQL-first & semantic layer tools
These tools start from SQL or from a governed model of your metrics. They suit teams that want one definition of "active user" or "revenue" shared by internal dashboards, customer-facing embeds, and AI assistants.
4. Metabase
Metabase is a popular open-source BI tool, with a visual query builder, a full SQL editor, and the Metabot AI assistant. Metabase 58, released in January 2026, reorganized its embedding options into modular embedding, which embeds individual pieces like dashboards or the query builder, and full app embedding, which embeds the whole app.
How you embed it
Modular embedding uses web components such as <metabase-dashboard>, or a React SDK. Guest embeds work on every plan, including open source. Embeds that sign customers in through SSO, which you need for per-customer permissions, require Pro or Enterprise. Tenant isolation uses row and column security, connection impersonation, or database routing, all on paid plans.
Pricing
The open-source edition is free to self-host. According to Metabase's pricing page, Pro costs $575 per month with 10 users included, then $12 per user per month, and "users of your embeds accessed through your product count as users." Enterprise starts at $20,000 per year.
Worth knowing
Metabase's row and column security docs warn that "Groups with native query permissions (access to the SQL editor) can bypass row and column security." If customers need SQL access, you'll handle isolation through database roles or separate databases instead.
Where it fits
Teams already running Metabase internally who want to extend it to customers, and who've modeled per-user costs at their expected scale.
5. Omni
Omni is a BI platform built on a semantic model, with SQL available wherever you need it. In October 2025, Omni acquired Explo, one of the better-known embedded analytics startups. Omni said Explo's platform would keep running for 12 months while customers migrated, so if you're evaluating Explo today, you're really evaluating Omni.
How you embed it
Your backend generates a signed SSO URL, using Omni's TypeScript SDK or HTTP API, and loads it in an iframe. Each customer gets a user attribute that drives an access filter on every query. Omni also supports a separate schema or database per customer. Its Create Mode lets embedded users build and share their own content inside their organization's folder.
Pricing
Omni doesn't publish prices. Expect a sales conversation.
Worth knowing
Omni's best practices list "Content built on SQL" among the things that won't render in embedded dashboards by default. You can expose it with AccessBoost, but Omni warns that "This has security implications, as you may expose data that you don't want your embed users to access."
Where it fits
Teams that want one governed model behind both internal BI and customer-facing dashboards, and who can work through a sales-led process.
6. Cube
Cube started as an open-source semantic layer and is still best known for that. You define your metrics once in code, and any frontend, BI tool, or AI agent can query them through SQL, REST, or GraphQL APIs. In October 2025, Cube merged its D3 agentic analytics product into its main platform, which now also includes workbooks, dashboards, and an analytics chat you can embed.
How you embed it
You have two options. Go headless and build your own UI on Cube's APIs, or embed Cube's dashboards and chat. For signed embedding, "Your backend generates a temporary session using the Cube API," and user attributes drive row-level security. Customers authenticate "without needing Cube accounts."
Pricing
Cube has a free tier. Starter costs $40 per developer per month, and Premium, which includes embedded dashboards and embedded chat, costs $80 per developer per month, according to Cube's pricing page. Embedded viewers aren't billed as seats. In Cube's words, "Our embedded analytics offering remains priced based on compute, as it always has been."
Worth knowing
You'll write the data model in YAML or JavaScript before anything works, and Cube's docs note that "usually one cube is created for each table." Signed embedding is limited to 10,000 external users unless you contact support. Compute-based pricing is also harder to estimate upfront than a flat fee.
Where it fits
Teams that want one metrics layer serving their product, their BI tool, and their AI agents, and that have someone to own the data model.
Developer-first & real-time API tools
These tools are for engineering teams that want analytics in their own codebase, rendered by their own frontend, often over high volumes of event data.
7. Tinybird
Tinybird is a managed ClickHouse service that turns SQL into production APIs. You write queries as "pipes," and Tinybird publishes them as REST endpoints that return JSON, CSV, NDJSON, or Parquet. It suits usage dashboards, metering, and other features that show fresh event data to many customers at once.
How you embed it
Data comes in through Tinybird's Events API or connectors for Kafka, S3, and GCS. Your backend signs a JWT with a fixed tenant parameter, and "Tinybird always uses the one specified in the JWT," even if someone edits the request. Because of that, your frontend can call the endpoint directly. Tinybird's homepage cites a Canva case study at 54 ms p99 query latency, though that's a vendor claim.
Pricing
The Free plan needs no credit card and includes 10GB of storage and 1,000 requests per day. The Developer plan card on Tinybird's pricing page shows $49 per month, while the same page also says "Starting at $25/month." SaaS and Enterprise plans are custom. Extra vCPU usage is billed by the second.
Worth knowing
There's no UI at all, so every chart is yours to build. Endpoints time out after 10 seconds by default, and a May 2026 changelog says shared plans have a platform limit of up to 600 queries per second.
Where it fits
Product teams with large volumes of event data who need fresh numbers in their app and have frontend engineers to build the charts.
8. Embeddable
Embeddable is a developer toolkit for in-app analytics. Your engineers define chart components, data models, themes, and access policies in code, then embed the result with a web component, <em-beddable>, that works in React, Vue, Angular, or plain HTML. There are no iframes, and the output is "Fully white-labelled by default."
How you embed it
Components are React components registered with defineComponent, and data models are defined in code on top of Cube. Your server requests a token with a securityContext, such as the customer's ID, and access policies use it to filter rows, tables, or schemas. According to Embeddable's row-level security docs, if a security filter can't be applied, the query fails rather than returning unfiltered data. Embeddable "does not replicate your database - it queries it directly."
Pricing
Embeddable doesn't publish prices. Its pricing page lists Startup, Scale-up, and Enterprise tiers on a flat monthly subscription, with "No usage-based pricing."
Worth knowing
Because it queries your database directly, speed depends on your database. Embeddable's docs advise setting the query concurrency explicitly for production connections, typically between 20 and 100. Its homepage advertises AI chat, but the docs describe the chatbot as "on the way."
Where it fits
Frontend-heavy teams who want analytics to look and behave exactly like the rest of their product, and who are happy to keep it in their codebase.
9. StarTree
StarTree is a managed version of Apache Pinot, the real-time database built for user-facing analytics at very high concurrency. Its homepage cites Stripe at "70ms p99 latency at 10k QPS," again a vendor claim. As of 2026, it can also query Apache Iceberg tables in place without ingesting them.
How you embed it
StarTree is a database, not an analytics product. You stream data in from Kafka or load it in batches, then your backend sends SQL queries and your frontend draws the charts. We didn't find end-customer row-level security in StarTree's docs, so plan to enforce tenant filtering in your own API layer. StarTree has a published partnership with Embeddable if you'd rather not build the UI from scratch.
Pricing
According to StarTree's pricing page, the fully managed SaaS option costs $0.21 per production vCPU per hour, with no separate charges for ingestion or storage. Bring Your Own Cloud costs $0.11 per vCPU per hour plus your own cloud bill. There's no free tier, but you can request a trial.
Worth knowing
StarTree's own 2026 Pinot overview is candid: "Pinot is not a magic layer that makes every arbitrary analytical query fast," and join performance still depends on how the data is laid out.
Where it fits
High-scale products where analytics latency under heavy concurrency is part of the product, backed by a team that can run a data platform.
How to choose a customer-facing analytics tool
Pick the approach first. If you want dashboards in front of customers this month and don't have frontend capacity to spare, start with an embedded platform. If you already care about governed metrics or run a semantic layer internally, start with that group. If analytics is a core product feature with high volume and real-time needs, start with the developer-first tools.
Then pick the tool:
- Choose Draxlr if your product runs on a SQL database and you want white-labeled dashboards, or a full self-service workspace, live in days at a flat price with unlimited embed viewers.
- Choose Luzmo if your customers want to build dashboards themselves with drag and drop, and the €1,995 monthly starting price fits your budget.
- Choose Qrvey if you have many tenants, need everything deployed in your own cloud, and want flat-rate pricing negotiated with sales.
- Choose Metabase if you already use it internally and per-user pricing works at your scale.
- Choose Omni if you want one governed model powering internal BI and customer-facing analytics.
- Choose Cube if you want a code-defined semantic layer that your app, BI tools, and AI agents all query.
- Choose Tinybird if you're serving fresh event data to many customers and can build your own frontend.
- Choose Embeddable if your engineers want analytics components in your codebase, rendered natively without iframes.
- Choose StarTree if you need sub-second queries at very high concurrency and can run a real-time database.
Still tempted to build it all yourself? Analytics work competes directly with your roadmap. In Sisense's vendor-commissioned 2025 State of Analytics research, reported by IntelligentCIO, 56% of organizations said analytics bottlenecks delayed product releases in the past year. Buying the analytics layer frees your team to work on the parts that are specific to your product.
Frequently asked questions
1. What's the difference between customer-facing analytics and embedded analytics?
They overlap heavily. Customer-facing analytics describes the audience, meaning your customers rather than your own team. Embedded analytics describes how it's delivered, inside another application. Most customer-facing analytics is embedded, but you can also build it from scratch on APIs, which is the developer-first approach in this guide.
2. Do I need a semantic layer for customer-facing analytics?
No. Tools like Draxlr, Luzmo, and Metabase query your database directly, so you can ship without a model. A semantic layer, such as a Cube data model or an Omni model, pays off when many dashboards, teams, and AI assistants need the same metric definitions. It does add modeling work before launch.
3. How do customer-facing analytics tools keep each customer's data separate?
Most use row-level security. Your backend signs a token that carries the customer's ID, and the tool adds a filter to every query before it reaches your database. Check that the filter also covers charts your customers build, SQL they write, and questions they ask an AI assistant, not just dashboards you built.
4. How much do customer-facing analytics tools cost?
Prices range widely. Metabase's open-source edition and the free tiers of Cube and Tinybird cost nothing to start. Draxlr starts at $75 per month flat, or $250 with row-level security, Metabase Pro at $575 per month plus per-user fees, and Luzmo at €1,995 per month. Qrvey, Omni, and Embeddable quote prices through sales.
5. Should I build customer-facing analytics in-house?
Only if analytics is your core product and needs something no tool supports. Otherwise, multi-tenant security, query performance, filters, exports, and white labeling are solved problems. Buying lets your team spend its time on which metrics to show and how they fit your product.
Bottom line
The right customer-facing analytics tool depends less on chart types and more on how much of the stack you want to own. Embedded platforms get dashboards in front of customers fastest. Semantic layers keep every metric consistent across your product and internal BI. Developer-first tools give you full control and real-time speed, as long as you build the interface yourself. Whichever you pick, test tenant isolation as a real customer would, and model the bill at the customer count you expect in a year, not the one you have today.
Sources
Pricing and product details for Luzmo, Qrvey, Metabase, Omni, Cube, Tinybird, Embeddable, and StarTree come from each vendor's own pricing page and documentation, checked on October 26, 2026.
- Draxlr, Pricing, Dashboard embed docs, and Full App Embed docs
- BARC, Data, BI and Analytics Trend Monitor 2026, November 2025
- Dresner Advisory Services, 2025 Embedded Business Intelligence Market Study, as quoted in a Qrvey press release, December 2025
- IntelligentCIO, coverage of Sisense's 2025 State of Analytics research, May 2025
