Knowledge Base Tech Stack 2026

Next.js with MDX handles rich documentation with interactive code examples, embedded videos, and structured content. Astro is purpose-built for content-heavy sites and ships zero JavaScript by default — exceptional Core Web Vitals for SEO. Docusaurus is the right choice for developer-facing documentation with versioning, search, and API reference integration. All three support static generation for maximum performance.

NestJS manages content APIs, user permissions, and the AI search pipeline. OpenAI embeddings power vector search — articles are embedded and stored in a vector database for semantic similarity search. Python with FastAPI is the alternative when the AI pipeline is complex (multi-model RAG, custom fine-tuned models). Sanity as a managed CMS handles content editing without building a custom CMS.

PostgreSQL with pgvector stores article embeddings alongside content metadata — no separate vector database needed for small-to-medium knowledge bases. Elasticsearch powers traditional keyword search with relevance scoring and highlighted snippets. Pinecone or Weaviate are appropriate when the embedding volume exceeds what pgvector handles efficiently (>1M documents) or when you need managed infrastructure.

Vercel's ISR (Incremental Static Regeneration) rebuilds individual articles on content change without full site rebuilds. Railway handles the AI search API. For knowledge bases with millions of monthly visitors, CloudFront + S3 static hosting is more cost-effective than Vercel at scale. Netlify is a simpler alternative with built-in form handling and deploy previews.