Are you looking for an embedded analytics BI tool, yet don’t know where to start and what to look for? This document provides a detailed comparison of popular embedded analytics tools, along with key criteria for evaluation.
The embedded analytics tools compared in this document are: Holistics, Looker, Tableau, Power BI, Metabase.
If you find any inaccuracies or have suggestions for improvement, please let us know using this form.
| Dimension |  Holistics |  Looker |  Tableau |  Power BI |  Metabase |
|---|---|---|---|---|---|
| Demo Playground | Not available | ✅ Available | ✅ Available | Not available | |
| Pricing Structure for Embedded Pricing is among the most important factors to consider when evaluating BI tools. A good embedded pricing should be easy to start when doing POC, as well as not be too expensive when you scale up. Typically embedded BI tools have pricing structure that scales with the number of embed viewers or usage of your application. Common pricing structures are:
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| Pricing Metric | Query runs/Query slots Select between Query Runs or Concurrent Workers. With unlimited dashboard viewers. (docs) | API calls One production instance, 10 Standard Users, 2 Developer Users, upgrades, up to 500,000 query-based API calls per month, and up to 100,000 administrative API calls per month. (docs) | Analytical Impressions Pay for entitlements of Analytical Impressions. Applies to users with the Viewer role. (docs) | Node Type & Node Instances Pricing based on node types and node instances. To publish content to an embedded capacity, at least one user requires a Power BI Pro license. (docs) | Feature-tiered Full-powered embedding starts from Pro plan ($500/mo). (docs) |
| Public Pricing | Pricing Transparency Transparent for standard plans. Contact sales for embedded pricing. | Pricing Transparency Opaque. Requires speaking to sales. | Pricing Transparency Transparent for standard plans. Contact sales for embedded pricing. | Pricing Transparency Transparent for embedded pricing. | Pricing Transparency Transparent for embedded pricing. |
| Embedding Methods Embedding methods affect the customizability of your embedded apps. Typically with higher customization, the tradeoff is higher development effort. Common embedding methods are:
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| iFrame Embedding | iFrame embedding Provide sandbox UI for generating the iFrame backend code (docs) | iFrame embedding Allow developers to generate signed embed URLs for dashboards, Looks, or Explores. (docs) | iFrame embedding Provide embed codes with configurable URL parameters for iframes on external applications. (docs) | iFrame embedding Create secure token-based URLs for iframes, with access controlled via Azure Active Directory. (docs) | iFrame embedding Allow users to generate signed URLs with tokens for secure embedding. (docs) |
| SKD Embedding | SDK embedding Not Available | JavaScript SDK Offers Embed SDKs for JavaScript, allowing developers to streamline embedding workflows. (docs) | SDK embedding Not Available | JavaScript SDK Provides a JavaScript SDK with pre-built functions for authentication, event handling, and embedded report interaction (docs) | React SDK Offers an Embedding SDK for React, allowing developers to integrate individual Metabase components. (docs) |
| API Integration | API embedding Not Available | Embed API Provides an Embed API that allows developers to programmatically control embedded content, such as dynamically generating embed URLs and interacting with Looker content within applications. (docs) | JavaScript API Provides a JavaScript API that allows developers to interact with embedded dashboards programmatically. (docs) | REST API Provides REST APIs that enable developers to programmatically retrieve embed URLs, generate embed tokens, and manage content. (docs) | Embed API Provides an embedding API that enables developers to fetch cards and dashboards via JSON Web Tokens (JWTs). (docs) |
| Public Embedding | Allow users to create a "shareable link" of a dashboard, and embed it directly to websites. (docs) | Public Embedding Allow users to share data visualizations publicly via embeddable URLs (docs) | Public Embedding Through Tableau Public, allowing users to publish visualizations to a publicly accessible server (docs) | Public Embedding Via "Publish to Web" option, which generates a publicly accessible embed URL for sharing reports without authentication. (docs) | Public Embedding Allow dashboards and questions to be shared via public links, which generate a shareable URL anywhere. (docs) |
| Permission & User Access Control Embedded tools should ensure each customer can only see their own data and prevents unauthorized modifications. This is called multi-tenancy. Most embedded BI tools support the basic version of this capability. When evaluating, look into permission levels (e.g., column-level access, row-level access, password-protected sharing) and ensure permission settings are intuitive. | |||||
| Multi-tenancy | Multi-tenancy Support row-level access controls managed through secure server-side tokens (JWT). | Multi-tenancy Supports Row-Level Access Control (RLS), and user attributes to securely segment data and tailor experiences for different tenants. | Multi-tenancy Supports site-level segmentation, user permissions, and Row-Level Security (RLS) to isolate data and content for different tenants. | Multi-tenancy Supports row-level security, user filters, tenant-specific configurations. | Multi-tenancy Supports row-level security via JWT tokens and multi-tenant deployments. |
| Dynamic Data Sources | Dynamic Data Sources Allow connecting to different data sources (databases) based on different customers (tenants). (docs) | Dynamic Data Sources Not supported | Dynamic Data Sources Not supported | Dynamic Data Sources Not supported | Dynamic Data Sources Not supported |
| Look & Feel The BI tools should allow developers to maintain a branding consistency, deliver customized dashboards and cater to diverse visualization needs. When evaluating, look into the level of customization for colors, fonts, layout. Assess the variety of chart types and their customizability. | |||||
| CSS & Custom Styles | Custom Theme and CSS Styling Allow users to create custom, reusable themes using code through canvas-based dashboard. (docs) |  Allow admin users to build and customize themes through LookML or UI settings. (docs) | Custom Themes & CSS Styling Supports indirectly via extensions and web embedding with CSS and JavaScript for advanced theming. (docs) | Custom Themes & CSS Styling Allow users to import JSON-formatted theme files. (docs) | Custom Themes & CSS Styling Available natively. (docs) |
| Custom Visualizations | Custom Visualizations Supports custom charts via Vega-Lite. (docs) | Custom Visualizations Available through Looker marketplace. (docs) | Custom Visualizations. Rich visualization options. Custom charts are supported with Viz Extensions API. (docs) | Custom Visualizations Supported with Power BI visuals SDK, limited native theme customization (docs) | Custom Visualizations Requires external tools or programming languages (e.g., Python with libraries like Seaborn or D3.js). (docs) |
| Custom Layout | Through canvas-based dashboard that allows more fluid dashboard design. (docs) | Custom Layout LookML Dashboards in Looker allow code-based customization of tile positioning, sizing, and settings. (docs) | Custom Layout Supports custom dashboard layouts with drag-and-drop, tiled or floating containers, flexible sizing, and Tableau extensions. (docs) | Custom Layout Allows custom layout definition via ICustomLayout and IPageLayout in embed configurations. (docs) | Custom Layout Limited support for custom layout via drag-and-drop interface to arrange charts, tables, and text cards on the dashboard. (docs) |
| Performance & Scalability Tools should ensures reasonable performance, and should scale well with increasing viewers and data volumes. There are typically 2 methods that affect report performance:
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| Query Caching | Query Caching Stores query results on demand for configurable durations. (docs) | Query Caching Stores query results and leverages persistent derived tables (PDTs) to precompute and cache aggregated or intermediate query results. (docs) | Query Caching Store query results in its in-memory data engine and utilizing a query cache on Tableau Server to improve data retrieval speed. (docs) | Query Caching Supports storing initial query results locally for semantic models in Import mode. (docs) | Query Caching Caches query results with configurable expiration for embedded dashboards. (docs) |
| Query Optimization | Query Optimization Via Aggregate Awareness. Automatically pick the most optimal aggregated tables per each query for maximal query performance. (docs) | Query Optimization Via Aggregate Awareness. Automatically pick the most optimal aggregated tables per each query for maximal query performance. (docs) | Query Optimization Via its Hyper data engine for in-memory computation, query caching, and pre-aggregated and Level of Detail (LOD) calculations to optimize queries. (docs) | Query Optimization Via Power BI user-defined aggregation, requiring users to manually define aggregation rules and mappings. (docs) | Query Optimization Via database indexing, caching query results, and allowing users to write custom SQL for precise and efficient data retrieval. (docs) |
| Self-service Report Creation Embed viewers should be able to customize and build their own reports based on a predefined set of data dimensions and metrics. Viewers should also be able to interact, download, and share custom reports with other embed viewers. When evaluating:
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| Self-service Exploration | Data Exploration Through a drag-and-drop interface within datasets, using filters, drills, native period comparison and curated dimensions and measures. (docs) | Data Exploration Through pre-built Explores, filters, pivoting, drill-downs, custom dimensions and measures. (docs) | Data Exploration Through a drag-and-drop interface, filters, pre-defined parameters, drill-down hierarchies, and natural language queries via Ask Data. (docs) | Self-Service Data Exploration Enables analysis with drill-throughs, slicers, filters, and natural language Q&A. (docs) | Data Exploration Through an intuitive interface that includes a graphical query builder, interactive dashboards, and a data browser for navigating databases and tables. (docs) |
| Alert & Scheduling | Alert and Scheduling Condition-based automated alert. Email/Slack scheduling is available in PDF/CSV format. (docs) | Alert and Scheduling Allow users to set data-driven alerts and schedule report deliveries via email, Slack, or webhooks. (docs) | Alert and Scheduling Through data-driven alerts for threshold notifications and automated schedules. (docs) | Alert and Scheduling Allows users to set up automated alerts, schedule extract refreshes and report deliveries. (docs) | Alert and Scheduling Enables users to configure notifications for specific data conditions, delivering updates via email or Slack at defined intervals. (docs) |
| Embedded Report Builder | Embedded Report Builder WIP feature. | Embedded Report Builder Not available yet. | Embedded Report Builder Through Embedded Web Authoring feature that enables end-users to create and modify reports within the embedded environment. (docs) | Embedded Report Builder Not available yet | Embedded Report Builder Through Interactive Embedding (Pro and Enterprise plans). (docs) |
| Security & Compliance Should protect your customers' sensitive data and builds trust by meeting industry security standards. Common security compliance certificates are: SOC2, HIPAA/BAA (for health tech companies), and GDPR. | |||||
| Compliance | SOC2, BAA, and GDPR compliant | SOC2, HIPPA, and GDPR compliant | SOC2, HIPPA and GDPR compliant | SOC2, HIPPA, and GDPR compliant | SOC2, CCPA, and GDPR compliant |
| Server Location | Servers in US (San Francisco), Europe (Germany), and APAC (Singapore). (docs) | Multiple locations in US, EU, APAC and Middle East. (docs) | Multiple locations in North America, Europe and APAC (docs) | Multiple locations across the world based on Azure regions. Default based on the region of signup. (docs) | US (East Coast), EU (Frankfurt), LATAM (São Paulo), and APAC (Singapore) (docs) |
| Maintainability Should allow the reuse of analytics logic and components across customers to reduce the maintenance burden for developers and product engineers. Common functionalities to support this are:
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| Semantic Modeling Layer | Semantic Modeling Layer Centralizes business logic in modular, reusable data models, allowing consistent definitions across reports. (docs) | LookML Data Modeling Enables defining centralized, modular data logic that can be reused across reports. (docs) | Logical Layer Properietary. Tableau's Logical Layer visually defines relationships and aggregation rules within workbooks or data sources. (docs) | Robust Modeling Project-focused and workbook-scoped, using visual interfaces and DAX for defining relationships and calculations, with limited global reusability unless datasets are explicitly shared. (docs) | Lightweight Modeling Layer Allows users to define metadata and create relationships between tables using joins directly in the query builder. (docs) |
| Analytics as Code | Code-based definition & querying languages (AMQL) Designed natively for 'analytics as code' workflow. Define models and dashboards using code, enabling components to be parameterized and reused. (docs) | Code-based definition language (LookML) Enables defining centralized, modular data logic that can be reused across reports. (docs) | Not supported No code-based definition language | Supported via TMDL format An object model definition syntax for tabular data models at compatibility level 1200 or higher. (docs) | Not supported. Product not designed to support code-based definition natively. Workaround using Serialization. (docs) |
| Version Control | Native Git Version Control Support Git version control natively for both dashboards and models. (docs) | Git-based Version Control Git-based version control for data models, proprietary dashboard versioning. (docs) | Properietary Version Control Supports version control indirectly by relying on Tableau Server or Tableau Online to maintain revision histories of published workbooks. (docs) | Proprietary Version Control No native Git integration. But new text-based format (TMDL) makes it easy for developers to set up manual integration with Git version control. (docs) | Properietary Version Control Proprietary. Allows one-way Git-based version control through Serialization, available starting with the Pro Plan. (docs) |
Discover what other practitioners are discussing about this topic.
Hi, we'd like to offer interactive dashboards for our customers. Each project will be quite unique, we need a solution that allows us to
jessillions Nov 2024 Metabase does all the things you list (I work here) www.metabase.com/product/embedded-analytics
Based on your requirements and the approx. number of clients needing access, I'd say <$10k is very realistic.
We just recently added an option to use Metabase with built-in storage, so you can also continue working with your data in excel.
Hi all, I'm currently researching for an embedded BI tool for my company use case. We need to provide embedded analytics to our customers (OOTB dashboards + self-serving capabilities).
trafalger Feb 2022 Hello! I'm a domo consultant and I have a client with an extremely similar use case - they're a software company who embeds Domo into their product and gives their customers more reporting using an embedded Domo. They sound extremely similar, they don't have a giant team but do most of the work themselves but reach out to us when they have questions. Only downside is the data refresh depending on how large/complex your data is, 15 mins is the standard refresh time. Happy to setup a quick phone call if you want to know more!
I searched far and wide but found nothing. I know how most people feel about Qlik, but what about using it for embedded analytics?
InitiativeOk6728 Sep 2024 Totally get your interest in Qlik for embedded analytics, but if you're open to alternatives, I'd suggest checking out Holistics.io (I work here).
Easy Embedding: You can embed interactive, pixel-perfect dashboards into your application with just a few lines of code. It's designed for a quick setup, usually taking only 30 minutes to an hour.
User Experience: Users can drill down into data and perform ad-hoc analysis, giving them more control and insights. Additionally, our unique canvas layout allows you to create beautiful, customized dashboards that match your application’s look and feel.
Pricing: We offer usage-based pricing, which can be more cost-effective compared to flat fees or consumption-based models, especially as you scale. You get unlimited users and only pay based on consumption.
Check out the playground and experience it for yourself: https://hooli.getholistics.com/
tl;dr: Questions: Which providers would you recommend / what is your experience with them and does it make sense to combine the BI tool with the embedded analytics solution?
nvqh Sep 2024 Probably late to the game, but you can check out Holistics.io (I work here).
• Version control with Git. Support software development process (CI/CD, dev prod environment, etc)
• Nice visualizations and flexible dashboarding
• Entire platform very programmable, you can do programming stuff with it
• Cloud-hosted
• Usage-based pricing instead of user-based.
• Email/Slack report schedules
My goal is to embed a tableau visualization I made from my tableau server onto my website and allow anyone who comes to my site to be able to view it. I have a tableau server creator's license and when I try to add the embed now, it works perfectly for me, but for everyone else, it wants a password to be able to view it.
86AMR Apr 2023 Tableau recently introduced a consumption-based licensing model for embedded analytics that is meant for external-facing use cases. I think this is what you need. If you are looking for something to truly be free then you will need to look at some of the open-source viz tools that are out there.
https://help.tableau.com/current/online/en-us/licenseproductkeys.htm
I'm using Metabase for embedded analytics and it's been great. It's easy to set up and has a lot of features that make it a good choice for embedded analytics.
We have tried quite a few tools for this. In production used Tableau but ran into issues: performance, dev complexity (write in desktop, not actual code!) even security bugs (leaking other customer data in filter choices!). Now we do double approach: in parallel implement prototypes with Quicksights, and for real average end-user use dont relay on any ready BI, but build "pixel perfect UX" in code using lower level UX dev (react) components. There are opensource ones, and we have created own inhouse set on top of these. One key learning is that the BI drill-downs and other fancy things are just too complex for embedded use cases in case of beginner and average users. Advanced users anyway dont want any UX, just "can i download my data" so they will use their looker/tableau/dwh stack or whatever.
Hey all, looking for some insight from those with experience of Sisense and Looker specifically in the world of embeddeding & monetizing within an enterprise web application. Here are some key things I’m looking for:
GeneralDouglasMac Feb 2019 Of the two: Sisense has the most functionality in multi-tenancy, row level security, and embedding. It is a bit dull on it's standard package but function over form there. Another suggestion I would consider (if you're asking) is Tibco Spotfire. Row level security, excellent embedding and server, the visuals are nothing to sneeze at at first but if you enable the D3.JS repository boy are the doors thrown wide open! It has about as capable GIS capabilities as any tool I've yet to toy with. I would NOT suggest DOMO. It has fallen by the wayside in support, feature matching, and costs compared to every other tool out there.
Hi all, I build and run a SaaS company. My customers want to analyze their data. I've built some charts for the most common analysis, but ideally I let the users build and manage their own visualizations and BI views. Does anyone have any recommended tools that might fit:
RomanSingele November 2023 Power BI Embedded with the A SKU (pay as you go) might be for you. You can scale up/down and even pause if you don't need it 24/7. The API let you do pretty much everything and you can play around with it in the playground.
Hi! My company is exploring a BI platform, ultimately to be embedded and geared toward external users.
The background is we have a product that generates a lot of data and allows users to explore it in a very specific way (think interactive video content based on an AI/computer vision pipeline on video) but there is no way for users to explore aggregate results (they can interact with particular videos but not see how many times X happened for example over a month worth of video)
burdenedwithpoipous April 2024 I don’t think this is asking for “a lot of free work”. This is very common and OP is smart to have realized, at least realized there’s some potential value, to buying over building. The most common, is why get in the business of maintaining the analytics, as an almost entire new product line, when your engineers are building your core product and so many vendors do BI well?
We went through this, and here is what we learned:
• never used Looker. But the LookML niche skillset and lack of resources in the market was a deal breaker for us.
• PowerBI was a cheap alternative to start. Not to different from LookML, the DAX become a bit unwelcoming but it worked for 100 users. When you scale, the feedback and requests become way more and you raised the important point of a potential future where you’ll let your customers be more self serving?
• we then turned to Tableau. While the price point was higher, it’s no doubt the easiest to use BI software. The talent market is massive, we were able to iterate quicker, and we have an upsell offering of self service analytics where we can still govern and control the data. Which is our IP. Really helped us serve more customers without bottlenecking our engineers.
You’ll have to explore the PowerBI to Big Query connection yourself. Not sure how that’s materialized recently considering the Google / MSFT competition and MSFT seems to be pushing Fabric really hard
Does anybody know of an affordable solution for embedded analytics that can be authenticated through your own application via the URL in an iframe or in some way where I can use embedded analytics and only have the data linked to the current logged in app user shown on the embed?
Grovbolle June 2021 Metabase perhaps or Apache Superset
We are using tableau now for embedded analytics, to share with our customers. We found the following issues:
Financial_Forky July 2020 I'm a Power BI guy. I interact with Tableau reports in our organization, but I've never used it to build one. While I like Power BI because it's what I know and am good at, both platforms should be able to handle 100+ million rows of data. Most of the modeling I do is on tables ranging from a few million up to 80 million rows, although I know Power BI is used successfully on data sets over 1 billion rows, but I suspect Tableau can, as well.
However, when you get to data sets of that size, you need to put a lot of thought into how you build your model. Are you following good star schema principles? Are you writing highly efficient measures and really understand the nuances of how different functions work? Sloppy code will work just fine on a 10,000 row table, but can grind to a halt at 10's or 100's of millions of rows.
My suspicion is that your performance issues aren't Tableau's fault, but rather just an indication of a sub-optimal schema and report design. It's entirely possible that a different technology may "fix" these problems for you just by the nature of how it is designed, but it could introduce new issues, as well.
I'm not specifically advocating that you switch to Power BI; I'm just suggesting that before you drop Tableau, you confirm that your performance bottleneck is Tableau itself, and not just your level of understanding of Tableau.
If this is "whitelabel embeds" vs publicly accessible, I've found all the "name brand" BI tools do this.
Honestly, the decision criteria for choosing are basically the same as a BI tool (SQL vs modeling, pricing, viz options).
The additional criteria being
• How much does customizability of branding matter to you
• How does their auth/sso/permissioning lifecycle work, and can your dev team handle it?
I'm using Metabase for embedded analytics and it's been great. It's easy to set up and has a lot of features that make it a good choice for embedded analytics.
Tableau used to / still has a framework with examples embedding in mobile apps, but as above its just a web element.
There are nuances to embedding for touch devices, the BI tool has to cater for the fact that you're not using a mouse to interact so actions like click and drag or right click need to be considered by the BI tool.
This is an interesting topic with no straightforward answer. There are a lot of factors involved with a decision like this:
• Where does your data live? If you use Google cloud services, you may get better deals/have an easier time using a Google BI product, etc.
• What OS do you and your company primarily use? If most people use macOS, then PowerBI is not a good option for you.
• What is your budget?
• What level of devops and data engineering support will you have?
There are open source tools that work well, but the setup and support might require a lot more engineering on your end. PowerBI is popular but a pain to use on macOS. Tableau/Looker/etc offer user control and embedded functionality built into their software, but the cost of user licenses can get very expensive depending on how many customers you have.
You might want to take a look at Holistics.io. It's a cloud-hosted, SQL-first BI platform with strong support for version control (Git) and a software dev workflow (CI/CD, dev/prod environments). The platform is highly programmable, and we offer pixel-perfect dashboards for precise reporting.
We also have usage-based pricing (not user-based) and built-in email/Slack report scheduling. If you're considering alternatives to PBI or Qlik Sense, Holistics could be a solid fit for embedded analytics.
Check out the playground: https://hooli.getholistics.com/