Learn more about exact and approximate kNN search in Elasticsearch, and when to use each one.

What is kNN?

Exact kNN: Search everything

Approximate kNN: A good estimate

Indexing for exact and approximate search

dense_vector field type

Quantization

How do I choose between exact and approximate kNN search?

Data size

Filtering

Future enhancements for kNN

Conclusion

Having less than 10 thousand documents to search could be an indication that exact search should be used. Approximate search scales better in terms of the number of documents, so it should be the preferred choice if you have a big number of documents or expect it to grow significantly.

How to choose between exact and approximate kNN search in Elasticsearch?

Exact kNN calculates the closer results by comparing all the existing document embeddings with the one for the query, ensuring accuracy but requiring more time. In contrast, approximate kNN provides an efficient approximation to kNN.

What is the difference between exact and approximate kNN search?

Elasticsearch kNN: How to choose between exact and approximate kNN search

How to choose between exact and approximate kNN search in Elasticsearch

Using the new semantic_text field type and semantic query for simplifying semantic search in Elasticsearch

semantic_text - You know, for semantic search!

What do you need to add semantic search?

Choosing an inference model

Creating your index mapping

Setting up indexing

Automatically handling long text passages

Querying your data

Under the hood

Customizing semantic text

Query customization

Data type customization

What's next?

Try it out!

Elasticsearch new semantic_text mapping: Simplifying semantic search

Author

Carlos Delgado

Articles

How to choose between exact and approximate kNN search in Elasticsearch

Elasticsearch new semantic_text mapping: Simplifying semantic search