Programming Tutorials

  The database ORM landscape has shifted. Two years ago, the decision matrix was simple: if you feared cold starts, you avoided Prisma. If you feared writing SQL, you avoided Drizzle. In 2025, the lines have blurred. Prisma’s introduction of  Driver Adapters  (Neon, PlanetScale, Turso) essentially solved the heavy Rust binary cold-start issue on serverless/edge environments. Meanwhile, Drizzle has gained massive adoption but hit a new, less documented scaling wall:  TypeScript Language Server (LSP) performance. We are now seeing large monorepos (500+ tables) using Drizzle where VS Code Intellisense lags by 2-3 seconds on every keystroke. This post addresses the current trade-off:  Prisma's memory footprint vs. Drizzle's type-inference cost , and provides a specific architectural pattern to fix Drizzle's compilation lag. The Root Cause Analysis Prisma: The Memory Tax Prisma generates a static  node_modules/.prisma/client/index.d.ts  file. When you query...