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Similarity Search and Embedding Storage

Similarity Search and Embedding Storage is the capability to find and retrieve similar items from large datasets using vector embeddings and efficient search algorithms.

Overview​

Similarity Search enables systems to:

  • Convert data into vector embeddings
  • Store and index high-dimensional vectors
  • Perform efficient nearest neighbor search
  • Scale to large datasets with minimal latency

Applications​

  • Recommendation systems
  • Semantic search
  • Content deduplication
  • Image similarity matching