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OpenSearch

As explained in Natural Language Processing in Action, Second Edition

OpenSearch is an open-source search and analytics platform with full-text, vector, and approximate-nearest-neighbor search capabilities.

OpenSearch is an open-source search and analytics platform suited to retrieval systems that need both conventional full-text search and vector-based similarity search. It provides a built-in vector database and approximate-nearest-neighbor (ANN) search, making it a turnkey alternative to assembling separate retrieval libraries. section 10.3.6

OpenSearch is positioned as a practical choice when:

  • You need full-text search alongside vector database and ANN functionality. section 10.3.6
  • You prefer a turnkey deployment over selecting among libraries such as Annoy, Faiss, and nmslib. section 10.3.6
  • You can manage Java packages and Docker containers, or want a more approachable experimentation path through Haystack. section 10.3.6
  • You are willing to review licensing changes and commercial-use restrictions in open-source infrastructure. section 10.3.6
Figure 10.5 Performance comparison of ANN algorithms for the New York Times dataset
figure

Compare ANN algorithm performance on the New York Times dataset before choosing a retrieval implementation or turnkey platform. section 10.3.6

How Natural Language Processing in Action, Second Edition covers it

How deep it goes
Defines capabilities and deployment tradeoffs but stops short of showing OpenSearch configuration or implementation code.
Examples
Uses an ANN performance comparison on the New York Times dataset as selection context.
What it assumes
Assumes retrieval and ANN terminology while flagging Java-package and Docker deployment as potential barriers.
What you can do after
Evaluate OpenSearch as a turnkey retrieval platform and weigh it against libraries or Haystack for experimentation.
How it connects
Connects full-text search, vector databases, approximate-nearest-neighbor search, Elasticsearch, ANN libraries, Docker, and Haystack.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Natural Language Processing in Action, Second Edition. The section links point to the parts of the book it draws on.