Struggling to choose between D.Buzz and Tokumei? Both products offer unique advantages, making it a tough decision.
D.Buzz is a Development solution with tags like database, modeling, erd, entity-relationship-diagram, open-source.
It boasts features such as Drag-and-drop interface for database modeling, Supports multiple databases like MySQL, PostgreSQL, Oracle, etc, Visualize database models through entity relationship diagrams, Generate SQL scripts for database creation, Reverse engineer existing databases, Customize visual theme and layout, Plugin architecture to extend functionality, Multi-user collaboration and pros including Free and open source, Intuitive and easy to use, Supports multiple databases, Visual modeling with ER diagrams, Generates SQL scripts automatically, Active community support.
On the other hand, Tokumei is a Online Services product tagged with privacy, selfhosted, analytics, opensource.
Its standout features include Self-hosted web analytics, Customizable dashboards, Event tracking, Pageview tracking, Real-time reports, Privacy focused - no user tracking, and it shines with pros like Open source and self-hosted for privacy, Customizable and extensible, Modern and easy to use interface, Active development and community.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
D.Buzz is a free, open-source database modeling tool used to design and visualize database models. It supports multiple databases including MySQL, PostgreSQL, Oracle, and more. D.Buzz provides an intuitive drag and drop interface to design Entity Relationship Diagrams and generate SQL scripts for database creation.
Tokumei is an open-source, self-hosted alternative to Google Analytics that allows users to track website traffic and analytics privately. It provides easy to understand analytics and visualizations without compromising user privacy.