Vector Database vs Full-text Search: Which Retrieval Should You Use?
Choose between vector search, full-text search, and hybrid search for AI retrieval systems.
Use vector search for semantic similarity, full-text search for exact terms, and hybrid search when users need both.
Fast answer
Vector search finds meaning. Full-text search finds exact terms. Real product search often needs both, especially in technical or enterprise domains.
| Decision | Choose vector search | Choose full-text search |
|---|---|---|
| Query style | Fuzzy meaning | Exact words, IDs, names |
| Data | Embeddings | Text index |
| Best for | Semantic discovery | Precise lookup |
| Common failure | Misses exact terms | Misses paraphrases |
| Mature pattern | Hybrid with reranking | Hybrid with semantic candidates |
When to choose vector search
Use vector search when users describe intent in natural language and the relevant document may use different words.
When to choose full-text search
Use full-text search when users search for exact product names, codes, error messages, people, document titles, or domain-specific strings.
Can they work together?
Yes. Hybrid search is often the practical answer. It catches semantic matches and exact matches, then can use reranking to improve the final order.
Common misconception
Vector databases do not make traditional search obsolete. They solve a different retrieval problem.