I find analytics that is not actionable in any way a waste of time. For example, checking the Insights Traffic pane on GitHub on your own repos to see how many people viewed your repo or cloned it.
Well implemented analytics will let you see how to optimize your system to serve some end goals better and for that you need data. As well as know from where the traffic is coming from.
If analytics are used, it's best to implement them server side with something like Netlify so as to not send unnecessary JS to the client and keep pages light.
Matamo - Open source alternative to Google Analytics.
LocustDB - Massively parallel, high performance analytics database that will rapidly devour all of your data.
Cube.js - Open source modular framework to build analytical web applications.
Analytics.js - Hassle-free way to integrate analytics into any web application.
OmniSci - Interactively query, visualize, and power data science workflows over billions of records.
Freshlytics - Open source privacy-friendly analytics software. It aims to be reliable, friendly to use and easy to deploy.
MixPanel - Analyze user behavior across your sites and apps. Then send messages and run experiments from what you learned–all in Mixpanel.
blackrock - Events & Analytics.
GoAccess - Visual Web Log Analyzer.
kSense - Insanely Fast Analytics.
Shynet - Modern, privacy-friendly, and detailed web analytics that works without cookies or JS.
Frovedis - Framework of vectorized and distributed data analytics.
AWS Web Analytics - Privacy-focused alternative to Google Analytics on AWS Pinpoint.
Microsoft Clarity - Analytics for Websites.
Splitbee - Friendly all-in-one analytics & conversion tool.
Analytics Zoo - Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray.
Panelbear - Fast and privacy-friendly website analytics.
Squzy - High-performance open-source monitoring, incident and alert system written in Go with Bazel.