Fast, relevant database search at scale
Databases weren't built for search. Elastic is. Offload search and analytics from your core systems and give users sub-second, relevance-ranked results.
Why database search needs more than SQL
Elastic complements your database by offloading search and analytics workloads, so your core systems stay fast and reliable. Databases are great for transactions — they weren't designed for search.
Here's what breaks and how Elastic fixes it.
What you can build with Elastic
Elasticsearch doesn't just match keywords — it understands and ranks them. It bridges keyword search, contextual semantics, and vector embeddings in one platform.
Customer and account search
Search users, accounts, and profiles with relevance ranking powered by BM25, tunable scoring, and boosting — not slow SQL queries.
Order, ticket, and record lookup
Find records instantly across large datasets with fuzzy search, synonyms, and typo handling backed by customizable analyzers.
Admin and internal tools
Enable fast search for support, ops, and analytics teams with faceted search and real-time aggregations across millions of records.
Hybrid search for AI applications
Layer semantic or vector search on top of database records using the piped ES|QL language and flexible query DSL for AI-powered experiences.
How Elasticsearch works
Elasticsearch transforms text into an efficient data structure called an inverted index, mapping terms to document locations so retrieval is blazing fast.
Works with the databases and tools you already use
Elastic indexes data from your databases and makes it searchable in real time. Index once. Search instantly.
