Search & Discovery (Elasticsearch/Meilisearch + Python/Node.js + Redis) overview

A search-centric architecture: Elasticsearch or Meilisearch provides full-text search with faceting, typo tolerance, and relevance tuning; Python or Node.js implements the indexing pipeline and query API; Redis caches frequent queries and handles rate limiting; and React renders the search UI with instant results, autocomplete, and filters. The indexing pipeline extracts, transforms, and loads documents from primary data stores (PostgreSQL, APIs, file systems) into the search engine. Meilisearch offers a simpler developer experience with instant indexing and good defaults, while Elasticsearch provides more advanced features like aggregations, nested documents, and distributed scaling. This stack powers e-commerce product search, documentation search, marketplace discovery, and internal knowledge base tools. The key tradeoff is maintaining index freshness: near-real-time sync between the source of truth and the search index requires careful pipeline design.