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Elasticsearch offers three main autocomplete strategies, each with unique benefits and trade-offs.

Choose Elasticsearch for complex text searches, but use databases for structured queries.

Optimizing Elasticsearch involves using filters, caching, and measuring performance.

Elasticsearch fuzzy search allows finding results even with typos in queries.

Elasticsearch offers two pagination methods: from & size for shallow pages and search_after for deep pages.

Deep pagination in Elasticsearch can slow down searches significantly, but there are efficient methods to handle it.

Filters check conditions without affecting relevance, while queries do.

Elasticsearch uses analyzers and synonyms to improve search accuracy by connecting similar words.

Elasticsearch distributes search queries across shards to find and retrieve results quickly.

Elasticsearch ranks search results using BM25 based on relevance scoring.