= Query vector data with CQL

To query data using Vector Search, use a `SELECT` query:

[source,cql]
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include::example$CQL/vector-search/vector-search-cycling.cql[tag=select-vector-data-cycling]
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To obtain the similarity calculation of the best scoring node closest to the query data as part of the results, use a `SELECT` query:

[source,cql]
----
include::example$CQL/vector-search/vector-search-cycling.cql[tag=select-vector-data-similarity-cycling]
----

The supported functions for this type of query are:

* similarity_dot_product
* similarity_cosine
* similarity_euclidean

with the parameters of (<vector_column>, <embedding_value>).
Both parameters represent vectors.

[NOTE]
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* The limit must be 1,000 or fewer.
* Vector Search utilizes Approximate Nearest Neighbor (ANN) that in most cases yields results almost as good as the exact match. The scaling is superior to Exact Nearest Neighbor (KNN).

* Least-similar searches are not supported.
* Vector Search works optimally on tables with no overwrites or deletions of the `item_vector` column. For an `item_vector` column with changes, expect slower search results.
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