Alex Cole

Convex provides automatic type safety all the way from your database schema to your React app. How does it work? Hint: we use some wild TypeScript.

Alex Cole discusses dynamic web apps, how serverless solutions compare to in-house stacks, and how product development changes when individual engineers can own features end-to-end.

Paginating over large datasets is tricky when the data is changing. Naive approaches result in missing or duplicated data. The trick is to rewrite limit queries (fetch 5 items) into range queries (fetch between cursors). Convex handles this automatically!

How do I ensure my Convex database queries are fast and efficient? When should I define an index? What is an index? This document explains how you should think about query performance in Convex by describing a simplified model of how queries and indexes function.

Relational databases are powerful tools for persisting data, but using them to build interactive web apps requires a lot of work. A web app architecture built on a relational database is an entire cluster of databases, backends, caching nodes, and Pub/Sub servers. And even after you invest in all of that infrastructure you'll still need to explicitly define your database schema upfront and write cumbersome SQL queries. At Convex we believe that web developers shouldn't have to worry about any of this. We can handle the servers, caching, and reactivity and you can focus on your product.

On Cloud Firestore, you'll have to do some acrobatics to integrate with React and listen for realtime updates. Down the road, you'll find your app full of slow loading experiences from request waterfalls and your database full of half-committed mutations.