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Everything about Vector database

Type of database that uses vectors to represent other data

A vector database, vector store or vector search engine is a database that stores and retrieves embeddings of data in vector space. Vector databases typically implement approximate nearest neighbor algorithms so users can search for records semantically similar to a given input, unlike traditional databases which primarily look up records by exact match. Use-cases for vector databases include similarity search, semantic search, multi-modal search, recommendations engines, object detection, and retrieval-augmented generation (RAG). Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Vector databaseA 5-minute orientation
  2. Skim a recent paper: SEVA 4.0: an update of the Standard European Vector Architecture database for advanced analysis and programming of bacterial phenotypesInfluential work since 2022
  3. Pick up a classic book: Longitudinal data analysisThe most-reprinted book on the subject
  4. Read the landmark paper: Survey of vector database management systemsCited 199 times
  5. Go sideways: Neo4jA closely related topic
  6. Go sideways: Couchbase, Inc.A closely related topic

📖 Definitions

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🗂️ The subject at a glance

  1. Techniques
  2. Applications
  3. Implementations

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics