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  1. A full text query that allows fine-grained control of the ordering and proximity of matching terms. The standard query for performing full text queries, including fuzzy matching and phrase or proximity queries. Like the match query but used for matching exact phrases or word proximity matches.

  2. Sonic can be used as a simple alternative to super-heavy and full-featured search backends such as Elasticsearch in some use-cases. It is capable of normalizing natural language search queries, auto-completing a search query and providing the most relevant results for a query.

  3. 20 Ιαν 2020 · search on exact values (numeric, range and keyword) Use queries for: ambiguous result (some documents suit more than others) full-text search; Unless you need relevance score or full-text search always try to use filters. Filters are “cheaper”. In addition, Elasticsearch will automatically cache the results of filters.

  4. 28 Σεπ 2023 · Full-Text Search: Elasticsearch is the go-to choice for building search engines for websites, e-commerce platforms, and content management systems. Its full-text search capabilities ensure that users can find relevant content quickly.

  5. In this section of the tutorial you are going to learn how to work with the full-text search capabilities of Elasticsearch. This will introduce you to several core topics such as working with the Python client library, creating and updating indices, making queries, and working with search results, all of which also apply to the more advanced ...

  6. 30 Αυγ 2023 · Today, we’re diving deep into Elasticsearchs strengths and exploring how it compares to traditional SQL and NoSQL databases. 1. Introduction to Elasticsearch. Elasticsearch, underpinned...

  7. 16 Μαΐ 2021 · Two options made sense to try out: PostgreSQL and ElasticSearch. Before diving down into my findings, let’s clarify the distinction between Full-Text Search (FTS) (or “Searching”) and database filters or queries. “Searching” involves starting with nothing and adding results to it.