Jupyter
Looker
Databricks
Google BigQuery
Presto DB
Rakam
Informatica
Concurrent
Trackboxx
Fathom Analytics
micro-analytics
Google Analytics
Plausible.io
Finteza
Nilly
ClickStory
Trackboxx is a simple and effective tool to record and evaluate visitors to your website. With Trackboxx we offer a clear and simple solution to evaluate what is happening on your website. No consent banner is required and is fully compliant with the Data Protection Act. The Trackboxx works without cookies and we do not store any personal data! This means that you don´t have to mention Trackboxx in any Consent Banner. So long as you are not using any other program that collects personal data, the Opt-in Option for example, Consent Banner is not required.
Jupyter TrackboxxTrackboxx's answer:
Trackboxx is the first privacy-first webanayltics, developed in germany. We offer several features in the realm of web analytics that our direct competitors do not provide. This includes, for example, the tracking of external links, and soon, the e-commerce tracking, which does not exist in any of our competitors' offerings. Additionally, the "userjourney" will soon be implemented, providing our customers with entirely new possibilities forweb analysis.
Trackboxx's answer:
In the realm of privacy-first web analytics offerings, the representations, visualizations, and evaluation capabilities are quite similar. We decided to take Trackboxx a step further - moving away from mere "data presentation" to genuine analysis. Furthermore, we've also chosen to incorporate additional features and functions into Trackboxx, such as a fully functional e-commerce tracking and a user journey that enables detailed analysis and evaluations.
Trackboxx's answer:
Our customers essentially come from all sectors and company sizes. We have many "smaller" clients who want to monitor their own websites, but we also have a multitude of agencies and marketing experts who oversee both their own projects as well as those of their clients. Moreover, well-known, reputable clients have now started to rely on Trackboxx, such as various banks and health insurance companies.
Trackboxx's answer:
Trackboxx was founded in 2020 and develops and distributes web analytics software as a SaaS solution. The idea emerged when it became increasingly difficult to use Google Analytics for our own projects as well as for client projects in a data protection-compliant manner. Thus, there was a desire to develop an in-house solution. It quickly became clear that there was a large market for such a solution, leading to the decision to develop Trackboxx as a full-fledged SaaS solution.
Trackboxx is compliant with data protection regulations and does not use cookies or process personal data. As a result, there is no need for a consent banner when using it on one's own website.
Trackboxx's answer:
Laravel, Angular, NodeJS, Clickhouse for our database
Trackboxx's answer:
Plausible Fathom Analytics Simpleanalystics
After quitting with google analytics i tested several solutions, like Matomo, plausible and simpleanalytics, i ended up with Trackboxx. Main reason was the clean dashboard that loads lighting fast. Another point was the roadmap - they are working (or already integrating) an e-commerce tracking what is very important for me.
I have been using Trackboxx for almost 2 years now and very happy with the data that I retrieve. The URL builder is a great addition to help support my marketing campaigns and the ability to set up goals!
Based on our record, Jupyter seems to be a lot more popular than Trackboxx. While we know about 216 links to Jupyter, we've tracked only 1 mention of Trackboxx. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / 3 months ago
LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 4 months ago
Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 5 months ago
Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 9 months ago
One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 12 months ago
Great to see so many alternatives! It would be great if we would get a spot on the list at some point. https://trackboxx.com/en/. Source: over 3 years ago
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Fathom Analytics - Simple, trustworthy website analytics (finally)
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
micro-analytics - Public analytics as a Node.js microservice 📈
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.