The Plan
For release 0.4, I decided to explore three things I kept hearing about but never really took the time to understand properly. The plan was to dive into Drizzle ORM, start contributing to Go codebases, and figure out what is MCP. I picked three different repositories to work with:
Drizzle ORM
I chose Drizzle because a lot of developers use it for handling database schemas and queries instead of writing raw SQL everywhere. The main reason I got interested because of my curiosity to databases. ORM stands for Object Relational Mapping. Basically it maps your code objects to database tables. Se…
The Plan
For release 0.4, I decided to explore three things I kept hearing about but never really took the time to understand properly. The plan was to dive into Drizzle ORM, start contributing to Go codebases, and figure out what is MCP. I picked three different repositories to work with:
Drizzle ORM
I chose Drizzle because a lot of developers use it for handling database schemas and queries instead of writing raw SQL everywhere. The main reason I got interested because of my curiosity to databases. ORM stands for Object Relational Mapping. Basically it maps your code objects to database tables. Setting up was straightforward. I activated Docker, cloned the repo, and started reading through the codebase. The architecture is pretty lightweight compared to other ORMs I’ve seen, which is probably why people like it. What I found interesting is how Drizzle lets you define database schemas in TypeScript instead of writing SQL queries scattered throughout your code. I’m planning to make some pull requests to Drizzle in the future. I want to understand how ORMs actually work under the hood. Contributing seems like the best way to learn that.
Streamplace
Streamplace is a project written mainly in Go and TypeScript. It’s a platform for live streaming and video processing - basically the infrastructure that handles live video streams. The backend performance-critical parts are in Go, and the more dynamic parts are in TypeScript. I got interested in this project because of how the code is organized. Coming from TypeScript projects where things can get complex because of high abstraction, seeing a well-structured Go codebase is really refreshing to me. I’ll write more about the specific contribution in my next blog post.
Tableau-MCP
Tableau-MCP is a project that makes it easier for developers to work with LLMs while building their projects. It provides resources and tools specifically designed for integrating AI models into your development workflow. The project is still in active development, which is actually why I wanted to contribute to it. It’s not in the last stages, it’s being built right now. I’ve been exploring the codebase and learning about MCP (Model Context Protocol). It’s a protocol for how applications interact with AI models. I’m planning to make contributions to this project. I’ll share the details in my next blog post.