Google Analytics (GA) is the most widely used analytics platform, with 50.3% of the top 1 million active websites using it today. You’re probably using it right now.
But despite being a free tool, Google Analytics is proprietary software, which means you’re handing over your browsing data, metadata and search history to a third party.
Do you trust them? We sure don’t.
This lack of control can lead to potential privacy risks and compliance issues. These issues have so far resulted in fines under the EU’s General Data Protection Regulation (GDPR) of an average of €2.5 million each, for a total of almost €6.6 billion since 2018.
Open-source analytics platforms offer a solution. They’re a safer and more transparent alternative that lets you retain full control over how you collect and store your customers’ data. But what are these tools? Where do you find them? And, most importantly, how do you choose the best one for your needs?
This guide explores the benefits and features of open-source analytics platforms and compares popular options, including Matomo, a leading self-hosted, open-source Google Analytics alternative.
What is an open-source analytics platform?
An analytics platform is software that collects, processes and analyses data to gain insights, identify trends, and make informed decisions. It helps users understand past performance, monitor current activities and predict future outcomes.
An open-source analytics platform is a type of analytics suite in which anyone can view, modify and distribute the underlying source code.
In contrast to proprietary analytics platforms, where a single entity owns and controls the code, open-source analytics platforms adhere to the principles of free and open-source software (FOSS). This allows everyone to use, study, share, and customise the software to meet their needs, fostering collaboration and transparency.
Open-source analytics and the Free Software Foundation
The concept of FOSS is rooted in the idea of software freedom. According to the Free Software Foundation (FSF), this idea is defined by four fundamental freedoms granted to the user the freedom to:
- Use or run the program as they wish, for any purpose.
- Study how the program works and change it as they wish.
- Redistribute copies to help others.
- Improve the code and distribute copies of their improved versions to others.
Open access to the source code is a precondition for guaranteeing these freedoms.
The importance of FOSS licensing
The FSF has been instrumental in the free software movement, which serves as the foundation for open-source analytics platforms. Among other things, it created the GNU General Public Licence (GPL), which guarantees that all software distributions include the source code and are distributed under the same licence.
However, other licences, including several copyleft and permissive licences, have been developed to address certain legal issues and loopholes in the GPL. Analytics platforms distributed under any of these licences are considered open-source since they are FSF-compliant.
Benefits and drawbacks of open-source analytics platforms
Open-source analytics platforms offer a compelling alternative to their proprietary counterparts, but they also have a few challenges.
Benefits of open-source analytics
- Full data ownership: Many open-source solutions let you host the analytics platform yourself. This gives you complete control over your customers’ data, ensuring privacy and security.
- Customisable solution: With access to the source code, you can tailor the platform to your specific needs.
- Full transparency: You can inspect the code to see exactly how data is collected, processed and stored, helping you ensure compliance with privacy regulations.
- Community-driven development: Open-source projects benefit from the contributions of a global community of developers. This leads to faster innovation, quicker bug fixes and, in some cases, a wider range of features.
- No predefined limits: Self-hosted open-source analytics platforms don’t impose arbitrary limits on data storage or processing. You’re only limited by your own server resources.
Cons of open-source analytics
- Technical expertise required: Setting up and maintaining a self-hosted open-source platform often requires technical knowledge.
- No live/dedicated support team: While many projects have active communities, dedicated support might be limited compared to commercial offerings.
- Integration challenges: Integrating with other tools in your stack might require custom development, especially if pre-built integrations aren’t available.
- Feature gaps: Depending on the specific platform, there might be gaps in functionality compared to mature proprietary solutions.
Why open-source is better than proprietary analytics
Proprietary analytics platforms, like Google Analytics, have long been the go-to choice for many businesses. However, growing concerns around data privacy, vendor lock-in and limited customisation are driving a shift towards open-source alternatives.
No vendor lock-in
Proprietary platforms lock you into their ecosystem, controlling terms, pricing and future development. Migrating data can be costly, and you’re dependent on the vendor for updates.
Open-source platforms allow users to switch providers, modify software and contribute to development. Contributors can also create dedicated migration tools to import data from GA and other proprietary platforms.
Data privacy concerns
Proprietary analytics platforms can heighten the risk of data privacy violations and subsequent fines under regulations like the GDPR and the California Consumer Privacy Act (CCPA). This is because their opaque ‘black box’ design often obscures how they collect, process and use data.
Businesses often have limited visibility and even less control over a vendor’s data handling. They don’t know whether these vendors are using it for their own benefit or sharing it more widely, which can lead to privacy breaches and other data protection violations.
These fines can reach into the millions and even billions. For example, Zoom was fined $85 million in 2021 for CCPA violations, while the largest fine in history has been the €1.2 billion fine imposed on Meta by the Irish Data Protection Act (DPA) under the EU GDPR.
Customisation
Proprietary platforms often offer a one-size-fits-all approach. While they might have some customisation options, you’re ultimately limited by what the vendor provides. Open-source platforms, on the other hand, offer unparalleled flexibility.
Unlimited data processing
Proprietary analytics platforms often restrict the amount of data you can collect and process, especially on free plans. Going over these limits usually requires upgrading to a paid plan, which can be a problem for high-traffic websites or businesses with large datasets.
Self-hosted tools only limit data processing based on your server resources, allowing you to collect and analyse as much data as you need at no extra cost.
No black box effect
Since proprietary tools are closed-source, they often lack transparency in their data processing methods. It’s difficult to understand and validate how their algorithms work or how they calculate specific metrics. This « black box » effect can lead to trust issues and make it challenging to validate your data’s accuracy.
11 Key features to look for in an open-source analytics platform
Choosing the right open-source analytics platform is crucial for unlocking actionable insights from your customers’ data. Here are 11 key features to consider:
#1. Extensive support documentation and resource libraries
Even with technical expertise, you might encounter challenges or have questions about the platform. A strong support system is essential. Look for platforms with comprehensive documentation, active community forums and the option for professional support for mission-critical deployments.
#2. Live analytics
Having access to live data and reports is crucial for making timely and informed decisions. A live analytics feature allows you to:
- Monitor website traffic as it happens.
- Optimise campaign performance tracking.
- Identify and respond to issues like traffic spikes, drops or errors quickly, allowing for rapid troubleshooting.
For example, Matomo updates tracking data every 10 seconds, which is more than enough to give you a live view of your website performance.
#3. Personal data tracking
Understanding user behaviour is at the heart of effective analytics. Look for a platform that allows you to track personal data while respecting privacy. This might include features like:
- Creating detailed profiles of individual users and tracking their interactions across multiple sessions.
- Track user-specific attributes like demographics, interests or purchase history.
- Track user ID across different devices and platforms to understand user experience.
#4. Conversion tracking
Ultimately, you want to measure how effective your website is in achieving your business goals. Conversion tracking allows you to:
- Define and track key performance indicators (KPIs) like purchases, sign-ups or downloads.
- Identify bottlenecks in the user journey that prevent conversions.
- Measure the ROI of your marketing campaigns.
#5. Session recordings
Session recordings give your development team a qualitative understanding of user behaviour by letting you watch replays of individual user sessions. This can help you:
- Identify usability issues.
- Understand how users navigate your site and interact with different elements.
- Uncover bugs or errors.
#6. A/B testing
Experimentation is key to optimising your website and improving conversion rates. Look for an integrated A/B testing feature that allows you to:
- Test different variations of your website in terms of headlines, images, calls to action or page layouts.
- Measure the impact on key metrics.
- Implement changes based on statistically significant differences in user behaviour patterns, rather than guesswork.
#7. Custom reporting and dashboards
Every business has unique reporting needs. Look for a flexible platform that allows you to:
- Build custom reports that focus on the metrics that matter most to you.
- Create personalised dashboards that provide a quick overview of those KPIs.
- Automate report generation to save your team valuable time.
#8. No data sampling
Data sampling can save time and processing power, but it can also lead to inaccurate insights if the sample isn’t representative of the entire dataset. The solution is to avoid data sampling entirely.
Processing 100% of your customers’ data ensures that your reports are accurate and unbiased, providing a true picture of customer behaviour.
#9. Google Analytics migration tools
If you’re migrating from Google Analytics, a data export/import tool can save you time and effort. Some open-source analytics projects offer dedicated data importers to transfer historical data from GA into the new platform, preserving valuable insights. These tools help maintain data continuity and simplify the transition, reducing the manual effort involved in setting up a new analytics platform.
#10 A broad customer base
The breadth and diversity of an analytics platform’s customer base can be a strong indicator of its trustworthiness and capabilities. Consider the following:
- Verticals served
- The size of the companies that use it
- Whether it’s trusted in highly-regulated industries
If a platform is trusted by a large entity with stringent security and privacy requirements, such as governments or military branches, it speaks volumes about its security and data protection capabilities.
#11 Self-hosting
Self-hosting offers unparalleled control over your customers’ data and infrastructure.
Unlike cloud-based solutions, where your customers’ data resides on third-party servers, self-hosting means you manage your own servers and databases. This approach ensures that your customers’ data remains within your own infrastructure, enhancing privacy and security.
There are other features, like analytics for mobile apps, but these 11 will help shortlist your options to find the ideal tool.
Choosing your self-hosted open-source analytics platform: A step-by-step guide
The right self-hosted open-source analytics platform can significantly impact your data strategy. Follow these steps to make the best choice:
Step #1. Define your needs and objectives
Begin by clearly outlining what you want to achieve with your analytics platform:
- Identify relevant KPIs.
- Determine what type of reports to generate, their frequency and distribution.
- Consider your privacy and compliance needs, like GDPR and CCPA.
Step #2. Define your budget
While self-hosted open-source platforms are usually free to use, there are still costs associated with self-hosting, including:
- Server hardware and infrastructure.
- Ongoing maintenance, updates and potential support fees.
- Development resources if you plan to customise the platform.
Step #3. Consider scalability and performance
Scaling your analytics can be an issue with self-hosted platforms since it means scaling your server infrastructure as well. Before choosing a platform, you must think about:
- Current traffic volume and projected growth.
- Your current capacity to handle traffic.
- The platform’s scalability options.
Step #4. Research and evaluate potential solutions
Shortlist a few different open-source analytics platforms that align with your requirements. In addition to the features outlined above, also consider factors like:
- Ease of use.
- Community and support.
- Comprehensive documentation.
- The platform’s security track record.
Step #5. Sign up for a free trial and conduct thorough testing
Many platforms offer free trials or demos. Take advantage of these opportunities to test the platform’s features, evaluate the user interface and more.
You can embed multiple independent tracking codes on your website, which means you can test multiple analytics platforms simultaneously. Doing so helps you compare and validate results based on the same data, making comparisons more objective and reliable.
Step #6. Plan for implementation and ongoing management
After choosing a platform, follow the documentation to install and configure the software. Plan how you’ll migrate existing data if you’re switching from another platform.
Ensure your team is trained on the platform, and establish a plan for updates, security patches and backups. Then, you’ll be ready to migrate to the new platform while minimising downtime.
Top self-hosted open-source analytics tools
Let’s examine three prominent self-hosted open-source analytics tools.
Matomo
| Main Features | Analytics updated every 10 seconds, custom reports, dashboards, user segmentation, goal tracking, e-commerce tracking, funnels, heatmaps, session recordings, A/B testing, SEO tools and more advanced features. |
| Best for | Businesses of all sizes and from all verticals. Advanced users |
| Licencing | GPLv3 (core platform).Various commercial licences for plugins. |
| Pricing | Self-hosted: Free (excluding paid plugins).Cloud version: Starts at $21.67/mo for 50K website hits when paid annually. |
Matomo Analytics dashboard
Matomo is a powerful web analytics platform that prioritises data privacy and user control. It offers a comprehensive suite of features, including live analytics updated every 10 seconds, custom reporting, e-commerce tracking and more. You can choose between a full-featured open-source, self-hosted platform free of charge or a cloud-based, fully managed paid analytics service.
Matomo also offers 100% data ownership and has a user base of over 1 million websites, including heavyweights like NASA, the European Commission, ahrefs and the United Nations.
Plausible Analytics
| Main Features | Basic website analytics (page views, visitors, referrers, etc.), custom events, goal tracking and some campaign tracking features. |
| Best for | Website owners, bloggers and small businesses.Non-technical users. |
| Licencing | AGPLv3. |
| Pricing | Self-hosted: FreeCloud version: Starts at $7.50/mo for 10K website hits when paid annually. |
Plausible Analytics
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Plausible Analytics is a lightweight, privacy-focused analytics tool designed to be simple and easy to use. It provides essential website traffic data without complex configurations or intrusive tracking.
Fathom Lite & Fathom Analytics
| Main features | Basic website analytics (page views, visitors, referrers, etc.), custom events and goal tracking. |
| Best for | Website owners and small businesses.Non-technical users. |
| Licencing | Fathom Lite: MIT Licence (self-hosted).Fathom Analytics: Proprietary. |
| Pricing | Fathom Lite: Free but currently unsupported.Cloud version: Starts at $12.50/month for up to 50 sites when paid annually. |
Fathom Analytics
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Fathom started as an open-source platform in 2018. But after the founders released V1.0.1, they switched to a closed-source, paid, proprietary model called Fathom Analytics. Since then, it has always been closed-source.
However, the open-source version, Fathom Lite, is still available. It has very limited functionality, uses cookies and is currently unsupported by the company. No new features are under development and uptime isn’t guaranteed.
Matomo vs. Plausible vs. Fathom
Matomo, Plausible, and Fathom are all open-source, privacy-focused alternatives to Google Analytics. They offer features like no data sampling, data ownership, and EU-based cloud hosting.
Here’s a head-to-head comparison of the three:
| Matomo | Plausible | Fathom | |
| Focus | Comprehensive, feature-rich, customizable | Simple, lightweight, beginner-friendly | Simple, lightweight, privacy-focused |
| Target User | Businesses, marketers and analysts seeking depth | Beginners, bloggers, and small businesses | Website owners and users prioritising simplicity |
| Open Source | Fully open-source | Fully open-source | Limited open-source version |
| Advanced analytics | Extensive | Very limited | Very limited |
| Integrations | 100+ | Limited | Fewer than 15 |
| Customisation | High | Low | Low |
| Data management | Granular control, raw data access, complex queries | Simplified, no raw data access | Simplified, no raw data access |
| GDPR features | Compliant by design, plus GDPR Manager | Guides only | Compliant by design |
| Pricing | Generally higher | Generally lower | Intermediate |
| Learning curve | Steeper | Gentle | Gentle |
The open-core dilemma
Open-source platforms are beneficial and trustworthy, leading some companies to falsely market themselves as such.
Some were once open-source but later became commercial, criticised as « bait-and-switch. » Others offer a limited open-source « core » with proprietary features, called the « open core » model. While this dual licensing can be ethical and sustainable, some abuse it by offering a low-value open-source version and hiding valuable features behind a paywall.
However, other companies have embraced the dual-licensing model in a more ethical way, providing a valuable solution with a wide range of tools under the open-source license and only leaving premium, non-essential add-ons as paid features.
Matomo is a prime example of this practice, championing the principles of open-source analytics while developing a sustainable business model for its users’ benefit.
Choose Matomo as your open-source data analytics tool
Open-source analytics platforms offer compelling advantages over proprietary solutions like Google Analytics. They provide greater transparency, data ownership and customisation. Choosing an open-source analytics platform over a proprietary one gives you more control over your customers’ data and supports compliance with user privacy regulations.
With its comprehensive features, powerful tools, commitment to privacy and active community, Matomo stands out as a leading choice. Make the switch to Matomo for ethical, user-focused analytics.
