[[term-level-queries]] == Term-level queries You can use **term-level queries** to find documents based on precise values in structured data. Examples of structured data include date ranges, IP addresses, prices, or product IDs. Unlike <>, term-level queries do not analyze search terms. Instead, term-level queries match the exact terms stored in a field. [NOTE] ==== Term-level queries still normalize search terms for `keyword` fields with the `normalizer` property. For more details, see <>. ==== [discrete] [[term-level-query-types]] === Types of term-level queries <>:: Returns documents that contain any indexed value for a field. <>:: Returns documents that contain terms similar to the search term. {es} measures similarity, or fuzziness, using a {wikipedia}/Levenshtein_distance[Levenshtein edit distance]. <>:: Returns documents based on their <>. <>:: Returns documents that contain a specific prefix in a provided field. <>:: Returns documents that contain terms within a provided range. <>:: Returns documents that contain terms matching a {wikipedia}/Regular_expression[regular expression]. <>:: Returns documents that contain an exact term in a provided field. <>:: Returns documents that contain one or more exact terms in a provided field. <>:: Returns documents that contain a minimum number of exact terms in a provided field. You can define the minimum number of matching terms using a field or script. <>:: Returns documents of the specified type. <>:: Returns documents that contain terms matching a wildcard pattern. include::exists-query.asciidoc[] include::fuzzy-query.asciidoc[] include::ids-query.asciidoc[] include::prefix-query.asciidoc[] include::range-query.asciidoc[] include::regexp-query.asciidoc[] include::term-query.asciidoc[] include::terms-query.asciidoc[] include::terms-set-query.asciidoc[] include::type-query.asciidoc[] include::wildcard-query.asciidoc[]