awesome-vector-database

Category: Curated Resource Lists
Tags: vector-databases, resources, tools, awesome-list

Description

A curated awesome list compiling resources, tools, vector databases, and research relevant to vector search and storage. Serves as a meta-resource for exploring the vector database ecosystem.

Source: https://github.com/mileszim/awesome-vector-database

Features

• Comprehensive List of Vector Databases: Includes both open-source and commercial vector databases for storing, managing, and searching high-dimensional data.
• Database Types: Covers databases that support various types of data and machine learning models.
• Key Database Entries:
  • Open Source: Faiss, Annoy, Milvus, HNSWLIB, NMSLIB, Cottontail DB, Vexvault
  • Commercial: Pinecone, Vespa, Vector.ai, Qdrant, Weaviate, NucliaDB
• Feature Overview:
  • Indexing methods (e.g., HNSW, IVF-PQ, LSH)
  • Query types (k-nearest neighbors, range search, reverse nearest neighbors, and combined queries)
  • Scalability and performance (distributed architectures, horizontal scalability, sharding, low query latency)
  • Integration with machine learning frameworks (TensorFlow, PyTorch, scikit-learn, etc.)
  • Support for various data formats (dense/sparse vectors, binary data, text, metadata management)
  • Security and privacy features (encryption, access control, compliance, backup and recovery)
• Use Cases and Applications:
  • Recommendation systems
  • Image and video retrieval
  • Natural Language Processing (NLP)
  • Anomaly detection
  • Molecular and drug discovery
• Related Resources: Additional references and links for further exploration of the vector database ecosystem.

Pricing

• Not applicable (resource list)