The Best Embedded Analytics Tools Available in 2025

Contents

Looking for an embedded analytics tool?

Embeddable embeds in minutes, loads in milliseconds and extends infinitely - enabling you to quickly deliver lightning-fast dashboards that feel native in your application...

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This guide is for people who are researching embedded analytics tools and want help to understand and evaluate all the options available.

Every customer-facing analytics project is different, so different tools and approaches can be suitable in some cases and not in others.

You’re in the right place if:

You have a project to build data visualizations (dashboards, reports etc.) into your application for your customers
You’ve not yet decided on a tool / approach yet

This guide aims to save you time and help you make the right decision in your evaluation of tools and approaches for your project.

What we’ll cover:

Why you might want an embedded analytics tool
What to consider when choosing a tool
Outline of the broad categories of embedded analytics tools
List of the top products in each category
And share some further reading, in case you’re interested

PS: We’ve done our best to keep this simple, transparent and objective in the pursuit of providing genuine help to you. We invite you to let us know if new tools, or new features in the tools listed, become available!

So, let’s get started!

TIMESAVING TIP: Read just the sentences in bold to get the TLDR.

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When to use an embedded analytics tool

If you’ve got one eye on your competitors, you know that providing seamless customer-facing analytics can help you to increase the value of your product or service to customers.

It’s a great opportunity to monetize your data: by turning it into actionable insights, showcasing the value of your product and supporting your customers to make informed decisions.

This usually manifests itself in the form of KPIs moving in the right direction, like increased sales, engagement, retention, and ultimately revenues.

Depending on your customers, supporting their decision-making with flexible dashboards and powerful data visualizations, directly within your user interface, could be a necessity to stay competitive.

But building data visualizations in code can be a deceptively complex and challenging project.

It makes sense. Even if you use a charting library, there’s a lot of logic and many moving parts that means even building a basic dashboard is hard.

But the worst thing about it is that every single improvement you (or your customers) ever want to make about the dashboard has to be done by a developer. That means it has to go through the product, onto the backlog, through sprint planning, code review, QA (maybe a few times) before it can be launched. That’s a huge time cost, but it’s also a huge opportunity cost vs. something else you could have built.

Embedded analytics tools are a way to fast-track the process and automate away the complexity of building, managing and maintaining dashboards and data visualizations in your app.

Related Guides:

Benefits of Embedded Analytics: User Engagement, Retention & Revenue.
What is Headless Embedded Analytics?
Rockset, ClickHouse, Apache Druid, or Apache Pinot? Which is the best database for customer-facing analytics?

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4 ways to add customer-facing analytics to your app

A lot of product and engineering teams get caught in the “buy or build” debate around customer-facing analytics: Do you buy an out-of-the-box solution or build it from scratch?

Until recently, those were your only options. But that’s changed with the introduction of a hybrid approach designed to give you the best of both worlds. Let’s take a look at all four main ways to get analytics into your app:

1. Build it yourself:

Since building your own analytics is very slow and complex (see previous section), and this article is really focused on exploring the tooling options available, we won’t go into more detail here. Instead, you’ll get a breakdown of the top solutions on the market, including BI platforms with embeddable components and dedicated embeddable analytics platforms.

2. Hybrid / headless embedded analytics tools:

Considered the ‘best of both worlds’ - a headless embedded analytics tool gives you all the benefits of other embedded analytics tools, but provides you with unlimited scope to extend its functionality and capabilities for your needs. By providing an SDK, a headless approach allows you to modify the style and functionality of the charts provided, in code, or bring in charts from any charting library of your choice.

3. Conventional embedded analytics tools:

This category contains only purpose-built embedded analytics tools. They typically include a dashboard builder tool with a set of charts, and they embed via an iframe or web component. Some of these tools are feature rich and can offer a very quick route to market, but they come with limitations around customizability and extendability.

4. Business intelligence (BI) tools with embedding features:

This category contains tools that were initially built for internal business intelligence. Those tools had existing dashboarding capabilities for internal use, which can now be embedded into front-end applications, typically via an iframe.

Whether you're building for business users who need more advanced analytics with multiple data integrations, or optimizing primarily for ease-of-use, scalability, or something else – there are lots of BI tools and dedicated analytics solutions to choose from and each have their trade-offs.

In this guide, we’ll cover all of the major approaches to displaying valuable data visualizations to your customers directly within your application.

‍We discuss popular embedded solutions, including their features, pros and cons, and the way they integrate into your app, to help you identify the best embedded analytics tools for you.

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Choosing the best embedded analytics solution

Whatever your business needs, from simple charts, to drill down capabilities, to natural language processing, to end-user self-serve, to a fully white-labelled embedded analytics solution, somewhere out there is a tool for you.

None of the tools in this guide is singularly ‘the best’ - it really depends on what you’re trying to achieve with the tool, and which stack you’re trying to implement it with.

How to choose an embedded analytics tool

We recommend following a process like this one below to evaluate the best tool for delivering your customer-facing analytics project.

Get clear on what you need ASAP: you’ll find it much easier to decide on the right tool if you have a solid understanding of what you’re looking for as early as possible. If you’ve got designs, or even a sketch that will help a lot. See the decision-making factors below.

Identify 3-5 tools to book a call with: by eliminating tools that don’t meet any of the hard requirements you established upfront, you’ll save a lot of time on your research process. Then you can book demos with the tools you think might be the best fit.

Run a proof-of-concept with 2-3 tools: when you’ve whittled it down to a small number of tools that match your requirements, we strongly recommend running a proof of concept (a PoC) with those tools. You never know what you might have missed in the research phase, or what someone misheard or miscommunicated in the sales process.

Make a decision: whether you’re a small business or a large enterprise, making a decision can be a quick or a long drawn-out process. Speak to the sales team at the tool you’ve chosen and they can often help you to push through your internal decision-making process by providing resources and providing assurances to other stakeholders.

Common decision-making factors

These are some of the most common reasons that a particular solution might be a good or a bad fit for your project - we’ll try to highlight these with each tool that we review in this guide, so you can quickly see what might be perfect, or a complete showstopper for you.

Data source compatibility: most tools connect to most common databases, but if you’ve got something non-standard or ‘bleeding edge’ that you don’t want to replace then this can be a great way to cut tools from the shortlist of options.
Embedding method (e.g. iframes): iframes are useful for many other jobs, but with embedded analytics they can have some drawbacks. They won’t feel like part of your application, you can’t pass values in and out of them, they might load slowly vs. other more modern methods like embedding via a web component. If you’re anti-iframe, then it’s good to know which tools require you to use them and which don’t.
Will it feel native?: If you want the experience to truly look and feel like it’s part of your application and align neatly with your design system - you really have two options: build it yourself or use a headless embedded analytics tool. If you’re willing to make a compromise here, then we recommend getting very clear on your requirements (including designs) and checking with each salesperson if their tool can deliver all of your needs.
Loading speeds: This one’s a key factor, but it often depends on your database to some degree. The best way is to test this in a proof-of-concept, but it’s good to look out for tools that have configurable caching options (as this will make it less important if your database is slow).
Specific features: this isn’t the place for us to list all of the features of every tool, but it’s worth doing a quick scan of the websites of tools you’re interested in if you need any of these features:
- End-user self-serve - for your end users to build/edit their dashboard views.
- Artificial intelligence tools - natural language querying, machine learning, ai-generated trend summaries etc.
- Email report scheduling - sending regular email reports to your users for you.
- Other - most tools come with exports, drill-downs etc. but make sure to check for anything you’re going to need.
Data security / sovereignty requirements: you may need to ensure data doesn’t travel outside of a certain region or environment. Check with compliance as soon as you can to see if you’ll need to self-host. This will enable you to quickly rule cloud-only providers.
Budget / pricing model: What you’ll end up paying for a tool often depends greatly on factors like the number of end-users, features included, white labelling, support levels, etc. With each tool offering its own licensing model - this one’s complicated. We recommend getting ballpark figures on the first sales call if you can, so that you can save time if something is going to be way too expensive.

Of course you'll also want a seamless integration and a user-friendly interface to build your embedded dashboards with. These factors can be subjective so we'll leave that for you to decide in the PoCs you run.

We try to cover each of the above factors, where information is available, for each solution and provide some customer feedback to help you navigate based on other people’s experiences.

Without further ado, here’s the list…

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The best embedded analytics tools in 2025

We’ve researched and compiled the key decision-making points about each of the top tools that were built specifically for customer-facing analytics.

Here they are…

1. Embeddable

Embeddable is a developer-first tool for building lightning-fast customer-facing dashboards. It uses a headless architecture to give you complete control over your user experience, and a performant data service to ensure that it loads fast, too.

Use Embeddable if:

You want dashboards to load fast
You want the experience to feel like part of your own application
You don’t want to be restricted to a limited set of charts
You want something scalable & extendable (so you won’t need to replace it later)

Out of the box, Embeddable gives you:

Embed any chart you can imagine - its unique headless architecture lets you extend the charts provided, in code, or bring your own charts from another charting library to achieve the dream experience for your customers.
Full control of your UX and UI - because you have full control in code, you can apply your own design system and make your product feel exactly like your designs.
A powerful no-code builder, which enables non-technical teams to craft and iterate upon your dashboards, using an intuitive point-and-click interface.‍
Fast, secure & simple embedding - via a performant web component that loads the charts natively in the DOM (no iframes!). This also enables bi-directional communication with your app, giving you even more control.
Lightning-fast loading - via a data service with 2 layers of built-in cache enables you to achieve sub-second loading times. Connections to data sources like ClickHouse and Druid and Pinot enable realtime data freshness.
Row-level security, multi-tenant support, built-in semantic later, configurable cache, React SDK, end-user self-serve, priority support options and more.

Embeddable launched in 2023 as the first headless embedded analytics tool on the market. It ran oversubscribed alpha and initial beta programs, won ‘Embedded Analytics Solution of the Year 2024’ at the Data Breakthrough Awards and raised a €6m round of funding in November 2024.

Its customers include a broad range of companies from startups to unicorns and enterprises doing over $1bn in annual revenue. Embeddable offers flat-rate pricing, letting you scale without worrying about costs or paying per user.

Embeddable connects to all major databases via a secure read-only transaction, and allows you to customize the caching refresh rate to ensure performance for your customer, whilst keeping your database server costs low.

Embeddable exists because we know, through years of experience, how complex it is to build great analytics experiences from scratch—and we believe that teams shouldn’t have to choose between undertaking an expensive, time-consuming custom build, or sacrificing the flexibility and performance they want for their customers by using a third-party tool.

What customers say about Embeddable:

"The impact on our development team has been immense." - Kaitlyn Lovatt, ‍Lead Product Manager at HONK

"Embeddable has enabled us to improve the experience for our users in a way and timespan that we wouldn't have achieved otherwise." - Bart Lammers, CTO & Cofounder at Eyk.

"The developer experience with Embeddable is excellent." - Pierre Vaidie, Head of Engineering at Pledge

To hear more customer feedback, and see the flexibility of what can be built with Embeddable, explore Embeddable’s Customer Stories.

Quick considerations:

Embedding method: Web component or Native React Embed enables you to embed in any frontend - React, Angular, Vue, Vanilla JS etc. or via a webview (essentially anywhere where there’s html).
Security considerations: Security as a first class citizen. Single or multi-tenant supported with row-level security. SOC2 Type II certified, GDPR compliant.
Performance (loading speed): performant data service with 2 layers of configurable cache to help you achieve sub-second loading speeds. Includes in-memory caching, pre-aggregations and connect directly to Cube to leverage your Cube cache if needed.
Customization freedom: Unlimited. If you can dream it, you can do it. Your end-users will also get customisable dashboards.
Hosting options: Cloud Hosted or Self-Hosted (enterprise only).
Pricing: Fixed, monthly subscription. Annual options are also available.
‍Data source compatibility: Amazon Athena, Amazon Redshift, Apache Pinot, ClickHouse, Databricks, Druid, DuckDB / MotherDuck, Elasticsearch, Firebolt, Google BigQuery, Hive / SparkSQL, ksqlDB, Materialize, Microsoft Fabric, Microsoft SQL Server, MongoDB, MySQL, Oracle, Postgres, Presto, QuestDB, RisingWave, SingleStore, Snowflake, SQLite, Trino and Vertica. It also connects natively to Cube’s semantic layer.

Apply for a spot on Embeddable's extended beta (limited spots available)

Building fully-bespoke dashboards with Embeddable

2. Sisense

Sisense was founded in Israel 2004, and as such is the most mature product on this list of solutions specifically designed for customer-facing analytics. It has all of the security certifications, extensive documentation and a community.

Use Sisense if:

You need a mature embedded analytics tool with a lot of features
You don’t mind too much about it feeling native in your app (iframes + limited customization)
You have a high budget and high LTV/ACV (because pricing is user/usage based)

What do customers say?

Users’ G2 reviews highlight the best things are “Ease of Use”, “Data Visualization”, “Customer Support”, “Easy Integrations” and broadly rate it well.

The main issues in the cons column include: “Learning Curve”, “Bugs”, “Missing Features”, “Slow Loading”, “Expensive” (in that order).

Quick considerations:

Embedding method: iframe embed
Security certifications: GDPR, CCPA, HIPAA, ISO 27701 & SOC2
Performance (loading speed): Sisense has a range of features to improve loading speeds for end users including in-memory cache, pre-aggregations etc.
Customization freedom: Apply theming, fonts and colours on a defined range of charts.
Hosting options: Self-hosted or Cloud-hosted options available.
Pricing: On-request - fixed pricing depending on your requirements and configuration.
Data source compatibility: Athena, Amazon Redshift, Azure Synapse, CSV, Databricks, Excel, Google BigQuery, Google Sheets, MongoDB, MySQL, Oracle, PostgreSQL, Salesforce, SingleStore, Sisense ElastiCubes, Snowflake and SQL Server.

3. Luzmo

Luzmo, formerly known as Cumul.io, is a Belgian-made out-of-the-box embedded analytics platform aimed at SaaS products. It’s specifically for customer-facing analytics and provides a set of charts that have configuration options that you can toggle in a user-friendly UI. It offers multiple options for how to embed.

Use Luzmo if:

You need to present data that’s served via an API endpoint (vs database connection)
You need to allow your end users to build dashboards themselves
You just need basic standard options with colours/theming applied
Your budget is >$2,000/mon (if you need white label)

Luzmo’s pride and joy is its self-service BI interface, which finds a nice balance between flexibility and simplicity. However, it’s highly curated so users still find that dashboards aren’t very customizable. Some have also found the documentation dense and difficult to use.

Its drag-and-drop interface is more simple and intuitive than many more-established BI platforms, but this comes as a result of a reduced feature-set and it’s not as strong as other no-code options when it comes to empowering non-technical users to get the most out of their data.

Luzmo also recently launched a conversational chatbot that returns trend data based on semantic inputs, so if you’re keen on embedding something AI-based into your tool, it might be worth exploring.

What users say about Luzmo

Users’ G2 reviews highlight the best things are “Ease of Use”, “Easy Integrations”, “Customer Support”, “Ease of Creation”.

The main issues in the cons column (in order) include: “Missing Features”, “Dashboard Usability”, “Complex Features”, “Dashboard Issues”, “Data Inaccuracy”.

Quick considerations:

Embedding method: Embed with a web component (renders as HTML in the DOM)
Security certifications: GDPR & SOC2.
Performance (loading speed): It’s relatively quick to load dashboards with its caching options and distributed CDNs.
Customization freedom: fixed set of out-of-the-box charts with limited customizations like colours and fonts. You also have to pay a higher price to take Luzmo’s branding out of your dashboard.
Hosting options: Cloud only (no self-hosting option is disclosed on its website)
Pricing: starts around $2,000/month for white label, scales with usage/users.‍
Data source compatibility: AWS Athena, Amazon Redshift, BigQuery, ClickHouse, Databaricks, Elastic Search, MariaDB, MongoDB, MySQL, Oracle, Panoply, PipelineDB, Postgres, Presto, SAP Hana, SQL Server, Snowflake, Stargod and Trino, plus a range of third-party integrations like Google Analytics, csv, and API connectors.

4. Vizzly

Vizzly is a new-to-market, low-code solution for building customer-facing analytics into your app. It’s ‘self-hosted first’ and has end-user self-serve they call ‘Custom Reporting’. Vizzly recently removed pricing from their site, but given it’s a relatively new tool, it might be a cheaper option vs. a more mature enterprise tool, and therefore, some might find it better suits their budget needs.

Use Vizzly if:

You want to self-host the platform on your own infrastructure
You need end users to be able to customize their own views of dashboards
You don’t like iframes
(+ you don’t require SOC2, ISO or HIPAA certifications)

Note: Vizzly was acquired by Gain Theory in November 2024 - customers reported some disruption as engineering headcount was significantly reduced during the transition. This may now be stabilized.

Already know that Vizzly's not right for your project? Find out about the best alternatives to Vizzly based on its limitations.

Vizzly makes a deliberate choice to avoid iframe, which has limited extensibility and means dashboards won’t interact with the rest of your app’s logic. Instead, Vizzly offers both cloud- and self-hosted options that can be embedded via React or using an HTML component:

Vizzly Lite: It allows users to upload data using a CSV rather than connecting to a database or API. They can then share or embed visualizations via URL.
Self-hosted: Lets users deploy Vizzly on their infrastructure using a command-line interface (CLI). This option works with most data sources including databases, GraphQL, or REST APIs.
(New) Cloud Option: Vizzly also now offer a cloud option they call ‘Cloud Query Engine’

With Vizzly, you can only choose visualizations from their library and apply a color, font or theme. So, if you want to add a label to the most recent data point on your line graph, insert a pop-up when someone hovers over it, or add any unique design ideas, you won’t be able to do it. Vizzly does also now support embedding via Angular, Vue, and Svelte.

What users say about Vizzly

“Super simple to set up, considering the query engine is self-hosted. We connected to our DB and set up a live dashboard a few hours after signing up. [But] the initial setup required a bit of developer effort before we could go live.”—Sryansh S, reviewed Vizzly on G2.

“Docs can be hard to follow at times but the general dev experience is solid. ” Naz M. reviewed Vizzly on G2.

Quick considerations

Embedding method: React Native or HTML
Security considerations: No certifications listed on site.
Performance (loading speed): Fast-loading with smart implementation - because you can choose which fields to group and the docker image doesn’t run the queries itself, it’s on you to ensure performance.
Customization freedom: fixed set of out-of-the-box charts with limited customizations like colours and fonts. No access to the code.Your end-users can get customisable dashboards.
Hosting options: Available for self-hosted only, which can be hosted on Google Cloud Platform (GCP), AWS, and Azure (though a cloud-hosted option is available if you just need to display data from an uploaded csv).‍
Data source compatibility: PostgreSQL, MySQL, Snowflake, Redshift, MariaDB, Google BigQuery, and SQL Server.

5. RevealBI

Reveal BI originally started as a traditional BI tool, but now it’s focused more on being a customer-facing embedded analytics tool. The product is now described as a purpose-built solution that integrates seamlessly into applications, so we’ve added it in this category.

It has a range of embedding and hosting options that may suit complex requirements and provides a menu of charting options that you can embed in your application.

Use RevealBI if:

You need a fixed price for the year (your user base fluctuates / is expected to increase.
You’ve run a PoC and you’re happy with the charts on offer (you can’t extend them)
You don’t need a high degree of flexibility

Given that the product pivoted from a more conventional BI tool to something designed for customer-facing analytics, it carries forward some of the drawbacks of a traditional BI tool with embedding options (like performance issues and limited customization options) that you can see in the main themes of the user reviews below.

What users are saying:

There aren’t so many reviews on G2, but in those which exist, users highlight the best things are “Intuitive”, “User Interface”, “Ease of Use”, “Data Analysis” and “Analytics”.

The main issues in the cons column (in order) include: “Limited Customization”, “Performance Issues”, “Poor Visualization” and “Slow Loading”.

Quick considerations:

Embedding method: use an iframe or use their SDK to render into the app itself.
Security considerations: SOC2 and GDPR Certifications.
Performance (loading speed): Reveal provides a caching layer to improve performance, but users report ‘performance issues’ / ‘slow loading’ as one of its main cons.
Customization freedom: Limited set of charts and customization options - theming can be applied in the builder, allowing configuration of things like “colors, fonts, and button styles”. No access to modify the code.
Hosting options: Self-hosted or Cloud-hosted options are available.
Pricing: Fixed, annual pricing - on request.
Data source compatibility: Amazon Athena, Amazon S3, CSV, Excel File, Google Big Query, Google Drive, Google Sheets, In Memory Data, JSON, MongoDB, MS SQL Server, MySQL, Oracle, PostgreSQL, REST, Snowflake.

6. Explo.co

Explo is a YC-backed startup providing a cloud-only service designed with a modern look and feel, optimized for market speed. Explo has everything you need IF you need what they have.

It provides a library of aesthetically pleasing charts, but you don’t have access to the code, so you can’t extend them yourself. However, customers have reported that they will sometimes offer to build features / new charts on request for you. They’ve also invested in an AI add-on which came to market in 2024.

Use Explo if:

You’re a startup that wants to go to market fast
Your design system / branding resembles their standard components
You want to embed AI-enabled dashboard features in your app (though this takes more time)
You don’t need to self-host in your own environment

What users are saying:

Users’ G2 reviews highlight the best things are “Ease of Use”, “Analytics”, “Customization”, “Customer Support” and “Time-saving”.

The main issues in the cons column (in order) include: “Bugs” “Software Bugs”, “Missing Features”, “Lack of Detail” and “Limited Customization”.

Quick considerations

Embedding method: iframe or web component
Security considerations: SOC2, GDPR and HIPAA
Performance (loading speed): Explo provides an in-memory cache powered by Redis & dashboard level caching for faster data responses.
Customization freedom: Limited - use the charts provided with styling/theming options.
Hosting options: Cloud Only. No self-hosted options available.‍
Data source compatibility: Amazon Athena, Azure SQL DB, BigQuery, Clickhouse, CockroachDB, Cube, CrateDB, Databricks, Materialize, Microsoft SQL Server, MySQL, Parade DB, Postgres, Redshift, Rockset, SingleStore, Snowflake, Supabase, Timescale, Tinybird.

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Business intelligence (BI) tools with embedding features

Should I choose a BI platform with an Embedding feature?

BI tools are great for helping you drive data-based decision making within the internal team, and were built from the ground up to serve that purpose.

What they weren’t built to do is to be the perfect tool for embedding beautiful, bespoke analytics into your platform. Which is why you and your customers need a solution that genuinely fits your needs.

Here are a few drawbacks of embedding analytics offerings from traditional BI tools:

Customization is limited: The charting components are ‘out of the box’ and you can’t change the code, which means you can’t modify them to really suit your customers’ needs. Want to add a data label on the last datapoint of the line graph? A tooltip when you hover over it? Edit the line thickness, or the transitions?... Well, you just can’t do it.
Slow loading and performance: You’ll often find your end user is staring at a loading wheel for much longer than you’d like them to. Why? These tools are built to run queries for internal teams who are happy to grab a coffee whilst a query runs in the background. They often don’t present data immediately for the end user (especially if you have a lot of data to analyze, or a complex query).
iframes: you’ll typically need to embed as an iframe, meaning you’ll lose control and the ability to deliver an integrated, native-feeling experience for your users.
Complex workarounds: BI tools are built for single-tenant architectures, and with user management in the web UI. Getting this to work in an embedded scenario with a multi-tenant architecture and without asking your users to log in twice often requires some unnecessarily complex extra work.
Price: The big BI tools are owned by the likes of Google, Microsoft and Salesforce. The brand reputation might be comforting, but it also comes with a sizable price tag. Depending on the pricing model, you might pay a huge annual fee, or you might find the pricing model scales very quickly with the number of customers you provide analytics to.

If you want to provide a great customer experience in your application, using a BI tool is probably not the route you want to take. You’d be better off using something built specifically for the use case.

If you’re thinking of going down the embedded BI tool route, we recommend you ask a few things first.

Nevertheless, here are the top tools in this category…

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1. Power BI Embedded

Power BI is a mature BI platform for businesses of all sizes. It’s a Microsoft product and it’s easy to use for everyone familiar with Office solutions. Power BI Embedded lets users use an iframe to incorporate its dashboards into their products. You’ll have to do some workarounds because the architecture was built for internal BI (e.g., multi-tenancy can be a pain,) but it’s enterprise-grade, has high security, and integrates with the Microsoft suite.

Use PowerBI Embedded if:

You’re ready for complexity
You’re wedded to the Microsoft ecosystem
You don’t mind if it loads fast, or whether it feels like part of your application
You want just one tool for both internal BI and customer-facing dashboards

If you're already using PowerBI, or are aware of it but not sure it's the right fit for you, check out our dedicated report on the best alternatives to PowerBI Embedded based on its limitations.

Power BI’s embedded analytics tool comes with multiple features to present end users with data analytics without much hassle, including:

Out-of-the-box visuals: Use your Azure-hosted data to build visualizations using Power BI’s library of certified components. Add your brand colors and logo.
Data security: Microsoft takes security very seriously and invests $1 billion a year on cybersecurity research and implementations alone, this makes user data protected from threats.
Documentation: whilst there’s a vast documentation hub on the site, it can be confusing and overwhelming, with information needed for one task spread across multiple pages.

While you can create interactive dashboards and organize the data as you want, you’re limited to Power BI’s out-of-the-box designs and charts. Plus, users say that Power BI isn’t as intuitive as you'd think, and it takes a lot of dedication to get dashboards up and running.

What users say about Power BI Embedded

In its reviews on G2, users highlight the best things are: “Ease of Use”, “Analytics”, “Data Visualization” and “Embedding Features”.

The main issues in the cons column (in order) include: “Initial Difficulty”, “Learning Curve”, “Learning Difficulty”, “Access Restrictions” and “Complexity”.

Quick considerations:

Embedding method: iframe.
Security certifications: Everything.
Performance (loading speed): Users flag this as one of Power BI’s issues, as larger datasets or complex queries can take a long time to load.
Customization freedom: Very limited. You can only change colors. fonts, and add your logo. It’s likely to be immediately obvious to your end users that this is a Power BI embed if they have used it before.
Hosting options: Power BI Embedded is a cloud service managed by Microsoft (note that Power BI Report Server is an on‐premises solution but is distinct from the Embedded service).
Pricing: ‘pay as you go’ - the price scales with how many virtual cores and GB of RAM you need (essentially, you’ll know when you get the bill). Learn more about Power BI Embedded Pricing here.
Data source compatibility: Amazon Redshift, Azure Analysis Services, Azure Blob Storage, Azure SQL Database, Azure Synapse Analytics, CSV, Dynamics 365, Excel, Google Analytics, Google BigQuery, JSON, Oracle, PDF, Salesforce, Snowflake, SQL Server, Teradata, XML.

2. Looker Embedded

Looker Embedded is an enterprise-grade BI platform that’s part of Google Cloud Core. It lets you come up with real-time loading user-facing analytics for your end users with high levels of security.

Use Looker Embedded if:

You’re wedded to the Google Cloud Core ecosystem
You want just one tool for both internal BI and customer-facing dashboards.
You don’t mind if it feels native in your application or not
You need enterprise-grade features
You have a large budget

Familiar with Looker Embedded and want something different? Check out our dedicated report on the best alternatives to Looker Embedded based on it's limitations.

Looker Embedded is a very powerful BI tool for enterprises that comes with a tonne of features and allows you to create integrated workflows with other tools from your stack. It also comes with these features:

Secure iframe settings. Enable your users to navigate your dashboards by embedding them into your app with an iframe. This way, users only access the requested data.
Self-service analytics. The iframe also provides you with interactive dashboards so your users can navigate, filter, and download data from your reports ad hoc.
Real-time loading dashboards. Make data available to end users live so they can see the metrics that matter the most to them.

Looker is one of the most powerful BI tools, but it falls on the expensive end (i.e. hundreds of thousands of dollars) and, like other tools, it lacks customization options. On top of that, it’s mostly suited for enterprises but can feel slow to load when processing large volumes of data.

What users say about Looker

There’s no dedicated G2 page for Looker Embedded, but if you scan the main Looker page on G2 for reviews, you’ll find a few themes popping up. The review of Alci H. in April 2024 captures a nice summary of the themes:

“Looker's ease of use has allowed us to provide it a self-service platform to all of our different product domain teams. Looker modeling is extremely easy to adopt. You can get powerful visualizations and dashboards with just a few clicks.” — BUT —“It's limited when it comes to pixel perfect reporting. It also has limitations with branding/theming capabilities. In addition, some of our users would like to use it for operational reporting use cases. The 5000-row limit has been a show stopper for a few of our customers.”

Quick considerations:

Embedding method: iframes.
Security certifications: Everything.
Performance (loading speed):
Customization freedom: Limited. You can only modify styling - e.g., changing colors, fonts, and add your logo. You do not control the code, and therefore must select from their library of charts.
Hosting options: Self-hosted and cloud-hosted available.
Pricing: Learn more about Looker Embedded pricing here.
Data source compatibility: Amazon Redshift, Apache Impala, Azure SQL Database, Google BigQuery, Greenplum, IBM DB2, MariaDB, Microsoft Azure PostgreSQL, MySQL, Netezza, Oracle, PostgreSQL, SAP HANA, Snowflake, Spark SQL, Teradata, Vertica.

3. Tableau embedded analytics

Tableau is known for its highly powerful BI tool – it provides depth of data exploration that the other major BI tools (Power BI, Looker etc.) can’t match. It has a high learning curve but is a tool of choice for data teams the world over.

It offers an iframe-based embedding option to enable you to present data in your application but the learning curve remains, and it suffers from some of the main issues of repurposed BI tools that we highlighted above, due to its architecture.

Use Tableau Embedded if:

You’ve already submitted the learning curve for using Tableau, and:
You want to connect to non-standard data sources
You want just one tool for both internal BI and customer-facing dashboards.
You don’t mind if it feels native in your application or not
You’ve got a large budget

Tableau is a data team’s ‘Swiss army knife’ but you wouldn’t use one of those to cut bread. This tool wasn’t really built for product and engineering teams to deliver customer-facing analytics, using a purpose-built tool would be a smarter move.

What customers say about Tableau Embedded:

Tableau as an internal BI tool has a bunch of great reviews on G2, and rightly so. But there aren’t many reviews of its embedding functionality.

Of the reviews available, its suitability for this use case is questioned by users like this Senior Product Manager who said: “Works well for internal BI usage, not for embedded analytics”, and also questioned on the speed/performance: “No internal cache layer, so gets slow when the data volume gets huge.”

Quick considerations:

Embedding method: iframe.
Security certifications: Everything.
Performance (loading speed): Users reports on performance vary, and there is no mention of any caching features in the Embedding API help docs.
Customization freedom: Lots of built-in features but can be overwhelming to configure. You cannot edit the charts in code, or bring in any custom designs you might want.
Hosting options: Self-hosted or Cloud-hosted. Tableau Server can be deployed on your own infrastructure (on‐premise or in a private cloud) to support embedded analytics
Pricing: Purchase Tableau license for internal builders PLUS viewers are $420 per year (annual billing only)‍
Data source compatibility: Amazon Athena, Amazon Aurora for MySQL, Amazon EMR Hadoop Hive, Amazon Redshift, Apache Drill, Apache Impala, Azure Data Lake Storage Gen2, Azure SQL Database, Box, Cloudera Hadoop, Databricks, Datorama by Salesforce, Denodo, Dremio by Dremio, Dropbox, Esri Connector, Exasol, Google BigQuery, Google Cloud SQL, Google Drive, Hortonworks Hadoop Hive, IBM BigInsights, IBM DB2, IBM PDA (Netezza), Kognito, Kyvos, MariaDB, MarkLogic, Microsoft Access, Microsoft Excel, Microsoft SQL Server, MonetDB, MongoDB BI Connector, MySQL, OData, OneDrive, Oracle, Pivotal Greenplum Database, PostgreSQL, Presto, Qubole Presto, SAP HANA (for virtual connections only), SAP Sybase ASE, SAP Sybase IQ, Salesforce, SharePoint Lists, SingleStore (formerly MemSQL), Snowflake, Spark SQL, Teradata, Text File, Vertica.

4. Metabase Embedded

Metabase is a very popular internal BI tool that became famous for its open-source offering that enabled teams to access a user-friendly business intelligence option for internal data analysis at an affordable price.

Now, it allows teams to embed their full BI tool into their applications (i.e., allowing deep data analysis by your end users within your application). They also offer ‘Static’ dashboard embedding, which is a robust tool but has a very opinionated UI – if you’ve seen one before, you’ll recognize a Metabase embedded dashboard immediately.

Use Metabase Embedded if:

You need to embed a ‘full BI tool’ into your own application with deep data discovery.
You want just one tool for both internal BI and embedded dashboards.
You don’t mind if it feels native in your application or not.
You have a high ACV (revenue per each of your customers)

What customers say about Metabase:

Metabase Embedded doesn’t have its own profile on G2, but the main Metabase G2 reviews page provides some insight into the performance and customizability of its offering. These are the most important things for a great user experience in an embedded setting – speed of loading affects users perception of your application, and without flexibility, it won’t look and feel like your application either.

The main issues in the cons column of its reviews on G2 (in order) include: “Initial Difficulty”, “Learning Curve”, “Limited Customization”, “Slow Loading”and “Slow Performance”.

Quick considerations:

Embedding method: iframe.
Security certifications: SOC2 Type II, GDPR.
Performance (loading speed): ‘Result and model’ caching to increase loading speeds.
Customization freedom: Limited - Metabase has one of the most opinionated UIs in the space. NOTE: They recently launched their SDK to give more control (in beta) however this essentially allows you to embed individual charts instead of only full embedded dashboards - it doesn’t give you additional control over the actual charts themselves.
Hosting options: Self-hosted or Cloud-hosted.
Pricing: White label option starts with a $500/month platform fee PLUS $10 per end-user per month (i.e. great if you have a small number of high-value customers, bad if you have many low-value customers)‍
Data source compatibility: Amazon Athena, Amazon Redshift, BigQuery, Databricks, Druid, MariaDB, MongoDB, MySQL, Oracle, PostgreSQL, Presto, Snowflake, Spark SQL, SQL Server, SQLite, Vertica

5. GoodData Embedded

GoodData is an internal BI tool with an embedding feature that allows you to take the dashboard you build in its UI and embed it into your application. It’s one of the only repurposed BI tools that allows you to embed as a web component vs. an iframe (meaning it will load natively in your DOM)

Use GoodData Embedded if:

You want to use one tool for both customer-facing analytics and internal BI
You want to avoid using iframes
The size of your user base is small/static

Quick considerations:

Embedding method: iframe, web component or via Javascript SDK
Security considerations: SOC2, CCPA, HIPAA, ISO 27001 and GDPR
Performance (loading speed): primary caching mechanism is called FlexCache, which stores query results in memory to help faster loading (use is limited per customer)
Customization freedom: Limited customization options on top of a limited range of charts.
Hosting options: Self-hosted or Cloud-hosted options available.
Pricing: On-request - users report that it scales with usage.‍
Data source compatibility: Snowflake, Amazon Redshift, Azure SQL, Google BigQuery, FlexConnect, Greenplum, Databricks, Microsoft SQL Server, PostgreSQL, Synapse SQL, Vertica, ClickHouse, MySQL, MariaDB, Oracle Database, SingleStore, GoodData ADS, MotherDuck, Dremio, and Apache Drill.

6. Sigma

Sigma is an internal business intelligence platform for data teams that was designed to work in a cloud environment. It offers the option to embed the dashboard you build in Sigma into your application using an iframe with a backend API connection.

Use Sigma Embedded if:

You’re using Sigma for your internal BI tool, and:
You’re happy with the charts they provide (you can’t extend them)
You don’t need to host on-premise in your own environment
You’re ok with iframe embedding

Not a fan of Sigma? We've listed the best alternatives to Sigma based on it's limitations here.

According to Sigma, embedding your first dashboard only takes a few hours, allowing users to access the data very quickly. Sigma offers:

‘Cloud-first for faster requests’: Sigma says that since you can run live queries against your cloud data warehouse without the need for data transfers, you get pretty immediate results. However, customers often report waiting long time periods for embedded dashboards to load, and having a spinning Sigma loading wheel in their charts whilst they wait.
Security features: Sigma works with both single- and multi-tenant setups. It supports row-level security, so you can define your own authentication preferences without providing a lookup to manage data access.
Simple components: Its Workbooks feature includes reusable data models, so you can easily pair them with the set of charting options available, without needing to write SQL queries.

Your team can embed a workbook, a single page (i.e. dashboard), or a single visualization (e.g. line graph), depending on your use case.

While you can change the colors and overall look of your embedded dashboards, as with all embedded BI tools the options are still limited and users have noticed a lack of visualization types—making it difficult to achieve the desired experience for your end users. On the whole, users agree with Sigma and believe the first integration is pretty fast and simple. But after that, creating dashboards or making ad hoc changes to reports can be more fiddly.

What users say about Sigma

“Sigma has many features that allow users of all development levels to get the most out of our data. While it’s simple to use, it sometimes lacks robust visualization options and the ability to customize how certain aspects of the chart look and feel”—Paxon F, Senior Data Scientist, reviewed Sigma on G2.

Quick considerations:

Embedding method: Sigma requires you to embed an iframe. This means that you can drop it into any frontend application, but you would need to also develop a backend API in order to connect.
Security certifications: GDPR, SOC2, ISO-27001, CCPA, DPF, HIPAA.
Performance (loading speed): Sigma claims to provide fast loading speeds but users are divided in their experiences.
Customization freedom: Limited. You can create ‘themes’ which allow you to edit colors, fonts, borders etc. across your analytics but you cannot modify the charts behaviors, add interactions or transitions because you cannot edit the code.
Hosting options: Cloud-based SaaS only. No self-hosting option.‍
Data source compatibility: AlloyDB, BigQuery, Databricks, MySQL, PostgreSQL, Redshift, Snowflake, and Starburst.

7. Trevor

Trevor is a business intelligence platform that allows non-technical team members to do their own reporting, even if they don’t know SQL. It also has embedded analytics capabilities powered by the same intuitive, no-code query builder. You can sign up and run a PoC without speaking to sales as they have a free tier that you can just login and use.

Use Trevor embedded if:

You’re building an initial proof-of-concept to validate embedding dashboards into your app
You don’t want to ‘speak to Sales’
You want to get it set up in a day
You don’t mind about the style of the user interface

Your team can build dashboards in an intuitive no-code environment. Then, when you want to load it in your application, you pass an identifier to Trevor which enables it to render the data specifically for that user. You control who can access what, and which filtering options are available on the embedded dashboards. You can read the developer docs here.

Key points:

Free tier & self-serve signup: no need to speak to sales. You can get yourself set up with the help of the docs.
Low-code setup, no-code iterations: Anyone on your team can build and iterate their own data visualizations using Trevor’s no-code query builder and drag-and-drop dashboard builder. Then, it’ll take an engineer less than an hour to embed the dashboard into your application.
Secure access: Trevor connects to your database using a secure read-only transaction, without taking a copy of your data. Customers log in via your app, not Trevor, and can only see the data you give them permission to see.
Responsive dashboards: Your dashboards update in real time, or whenever you configure it to, allowing users to confidently access fresh, accurate data insights.

Trevor is a great BI platform that has helped a lot of businesses take actionable insights from complex data. The dashboard embedding functionality is really easy to use and many customers say they love the aesthetics of the charts and dashboards (to which you can apply your brand’s color palette). But, because it provides you with a charting library and a degree of customization out of the box, it doesn’t allow you to bring the individual charts into your own code repo. So, it’ll never be quite as flexible as something you build yourself - which is why we built Embeddable.

Quick considerations:

Embedding method: Trevor allows you to embed your dashboard using an iframe or a simple JS snippet which enables you to embed it into any frontend application with minimal engineering effort.
Security certifications: GDPR.‍
Performance (loading speed): Fast-loading—Trevor calls your database directly, so it will be fast if your database is able to respond in good time, but may be slow if your server response takes some time. ‍
Customization freedom: Limited. You can apply your brand’s color palette, but the charts themselves are not customizable in CSS. ‍
Hosting options: Self-hosted and cloud-hosted options available. Works on-premise if you’re using AWS, Google Cloud or Microsoft Azure.
‍Data source compatibility: Amazon Redshift, BigQuery, MariaDB, MySQL, PostgreSQL, Snowflake, SQL Server.

8. Domo Analytics

Domo is an internal business intelligence tool that’s been around for a while, so has a broad feature set and robust infrastructure - but its architectural approach means it has similar limitations to other BI tools with its embedding features.

Quick considerations for Domo:

Embedding method: iframe embedding with JS controls.
Security certifications: GDPR, HIPAA, SOC 1/2 and ISO standards.
Performance (loading speed): in-memory cache provided alongside pre-aggregation options.
Customization freedom: Limited customization on the set of charts provided - “including colors, logos and visualization elements.”
Hosting options: Cloud SaaS only.
Pricing: Tiered, credits based pricing that scales with your usage. There are different support and security offerings per tier. Quote on inquiry.
Data source compatibility: Amazon Athena, Amazon Redshift, Apache Druid, Google BigQuery, MariaDB, Microsoft SQL Server, MySQL, Oracle, PostgreSQL, Snowflake

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9. Qlik

Qlik is a suite of analytics tools built around a core BI tool, its embedded analytics offering shares the limitations that other BI tools have when embedding – because it was built for internal BI and then repurposed. If you are using the broader suite of its tools, then it can be an easier option to use this tool vs. finding a purpose-built solution.

Quick considerations for Qlik:

Embedding method: iframes.
Security certifications: Everything.
Performance (loading speed): varies across their different pricing plans (only enterprise plans qualify you for the Rolls-Royce engine)
Customization freedom: Limited set of charting options, no access to modify in code or apply your own design system.
Hosting options: Self-hosted or Cloud-hosted.
Pricing: $30,000/year platform fee with limited data throughput (50gb/year) and 100,000 viewers included. You’ll need to upgrade to enterprise for their higher degree of performance.
Data source compatibility: Amazon Athena, Amazon Redshift, Apache Drill, Apache Hive, Apache Phoenix, Apache Spark, Azure SQL Database, Azure Synapse Analytics, Cloudera Impala, Databricks, Google BigQuery, IBM DB2, Microsoft SQL Server, MongoDB, MySQL Enterprise Edition, Oracle, PostgreSQL, Presto, Snowflake, Sybase ASE, Teradata

10. Omni

Omni is an interesting, new-to market BI tool from the team behind Looker - it offers an embedding option but its feature set is most likely limited vs other embedded analytics tools due to its maturity.

Embedding method: iframes only.
Security certifications: SOC 2 Type II, GDPR, CCPA, and HIPAA.
Performance (loading speed): Limited user reviews make this hard to determine, it would need to be tested as part of a PoC.
Customization freedom: Limited to the set of charts available in the dashboard builder.
Hosting options: Cloud-based SaaS only. No self-hosting option.
Pricing: No information is disclosed on the website - there is a free trial (on request) and it claims to not to have ‘an enterprise price tag’.
Data source compatibility: BigQuery, ClickHouse, Databricks, Microsoft SQL Server, MotherDuck, MySQL, Postgres, Redshift, and Snowflake.

You’ll see in the screenshot of the Omni website below that two examples of what customers had built in Omni were essentially the same dashboard with colours switched out, which indicates that the degree of flexibility in the platform is likely not quite there yet for an embedded dashboard use case.

Summary

1. Don’t build it yourself, unless:

You have super custom requirements and none of the tools can help you
You need something very, very simple that you expect to replace later
You have access to unbelievably cheap product and engineering resources

Even with charting libraries on hand, building your own solution is very time-consuming. It takes a lot of work to create custom components that match your requirements, and that’s before you’ve considered factors like handling languages/currencies/timezones, performance and loading speeds, interactions between charts, or row-level security.

2. Try Hybrid / Headless if:

You want it to load fast
You want it to feel like your own application
You don’t want to be restricted to a limited set of charts
You want something scalable & extendable (so you won’t need to replace it later)

Instead of “buy or build” you get to embed a fully bespoke, fast loading experience to your customers without the cost of a custom build or the constraints of traditional embedded analytics tools.

‍Embeddable is the leading hybrid embedded analytics tool - it was the first to adopt a headless architecture and was built from the ground up to enable teams to quickly embed analytics with unlimited customization freedom, in code. It’s built specifically for customer-facing analytics, so it enables you to achieve sub-second loading times for users too.

3. Use an off-the shelf embedded analytics tool, if:

You want the shortest time to market
You have little/no engineering resources to spare
You don’t mind if it doesn’t feel exactly like it’s your own application
You are content with the range of charts on offer (you can’t extend them)

You can get embedded analytics by paying for an out-of-the-box solution. It has a shorter time to market than building it from scratch, but the main drawback is the lack of customization (and sometimes performance). You only get a stock set of charting components that won’t look and feel like your app; and you’ll have no option to bring in your own custom charts.

4. Use a business intelligence tool with embedding features, if:

You’re already using the BI tool for internal analytics and…

The look and feel in your application is not important
Loading speeds do not need to be sub-second
You don’t mind loading through iframes

Or you simply need the peace of mind you get with choosing something from suppliers like Google, Microsoft and Salesforce.

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Frequently asked questions

What is an embedded analytics platform?

An embedded analytics platform is dedicated software that can integrate data analytics or dashboards into an app for end users. That means users can find data insights right within the app they already use, rather than switching to another platform. Examples of embedded analytics platforms include Embeddable, Looker, and Luzmo.

Why use embedded analytics?

Use embedded analytics to raise the perceived value of your product and increase customer engagement. You can also use it to monetize data since a lot of customers are happy to pay to access data that helps them make informed decisions about their business, operations, and activities. Typically, you’d choose an embedded analytics solution if you wanted to deploy analytics more cheaply and quickly than building them from scratch.

What’s an example of embedded analytics?

Here’s an example of embedded analytics: Imagine your product is a no-code website builder. You might embed analytics into your platform so that users can see how their site is performing and make data-driven decisions about their business. This would keep them engaged with your app, rather than having them go to Google Analytics to see metrics like site visitors, bounce rate, and goal completions.

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References

1. Embeddable – https://docs.embeddable.com/. 2. Sisense – https://support.sisense.com/hc/en-us/articles/360001928438-Data-Connectivity 3.Luzmo – https://docs.luzmo.com/data-connectors. 4. RevealBI – https://docs.revealbi.com/admin/data-connections. 5. Explo.co – https://docs.explo.co/integrations. 6. GoodData – https://www.gooddata.com/documentation/data-integration. 7. Vizzly – https://docs.vizzly.co/connect-data-sources. 8. Power BI Embedded – https://learn.microsoft.com/en-us/power-bi/connect-data/desktop-data-sources. 9. Looker Embedded – https://docs.looker.com/setup-and-management/connecting-to-db/connecting-database. 10. Tableau Embedded Analytics – https://help.tableau.com/current/pro/desktop/en-us/data_connections.htm. 11. Metabase Embedded – https://www.metabase.com/docs/latest/embedding/start. 12. Trevor – https://guide.trevor.io/hc/en-us/articles/360015196659-Connect-your-database. 13. Domo – https://www.domo.com/data-integration/connectors. 14. Qlik – https://help.qlik.com/en-US/connectors/Subsystems/Connectors/Content/Connectors/About-Connectors.htm. 15. Yellowfin – https://wiki.yellowfinbi.com/display/user80/Connecting+to+Data. 16. Omni – https://docs.omni.com/connectors. 17. Sigma – https://support.sigmacomputing.com/hc/en-us/articles/360044121653-Connecting-to-Data