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ai deep-dive

pgvector Deep Dive: Bringing Vector Search Back into PostgreSQL

pgvector is a PostgreSQL extension, not a standalone vector database. It adds exact and approximate vector search to the same data model, transactions, and operations stack, while leaving index tuning and horizontal scaling as PostgreSQL concerns.

Neon vs Turso: Do Not Call Both Serverless Databases Managed Postgres

Neon is serverless PostgreSQL; Turso Cloud currently follows the libSQL and SQLite-compatible path. Their compatibility boundaries are fundamentally different.

Nhost: A BaaS of PostgreSQL, Hasura GraphQL, Auth, and Storage

Nhost uses PostgreSQL as the source of truth, Hasura to generate GraphQL, and connects Auth claims, role permissions, Storage, and Functions into one platform.

Supabase: A Platform Built Entirely on PostgreSQL

Supabase isn't just an open-source Firebase alternative — its core design builds Auth, Storage, and Realtime entirely on PostgreSQL schemas and WAL. The result: everything is queryable with SQL, pgvector works out of the box, and AI agents can operate the entire platform by writing SQL. 108k GitHub stars, Apache 2.0, free tier with 500 MB database.

tech deep-dive

Is PostgreSQL Really Enough? Don't Rush to Adopt Specialized Databases

Most teams don't need five databases. PostgreSQL's extension ecosystem covers caching, queues, full-text search, and vector search — but the real decision isn't 'can it do it' but 'where does ops cost cross performance needs.'

tech guide

Prisma ORM: Type-Safe Database Access for TypeScript Projects

Prisma's schema-first design gives you versioned migrations, full TypeScript types on every query, and intuitive relation handling. The tradeoff is a learning curve and the inherent limits of any ORM abstraction — but for most TypeScript projects, it's a worthwhile deal.

tech guide

From Mock to Real AI: Integrating Cloudflare Workers AI into action-maker

Upgraded action-maker from hardcoded mock data to live Cloudflare Workers AI generation. The architecture splits into Worker (AI only), Server (data storage), and Frontend (orchestration). Hit two gotchas along the way: Qwen3's thinking block and the Workers AI response format.

tech deep-dive

DaoDao Tech Architecture: Monorepo, Multi-Language Backend, and AI Recommendation System

Next.js + Expo frontend, Node.js + Python dual backend, PostgreSQL + Redis core — plus a social notification system and LLM recommendation engine. Here's how DaoDao builds a learning community platform with a modern tech stack.