Search use case
Serverless Stack
This section documents Elasticsearch search primitives. These capabilities are available across all Elastic deployments.
Use this section to understand search techniques, query methods, ranking strategies, and data ingestion for search applications.
Using the Elasticsearch solution or serverless project type? The Elasticsearch solution documentation covers additional UI tools that complement these search primitives. Refer to Elasticsearch solution & project type overview for more details.
Use Elasticsearch search primitives to build search applications including:
- Website and documentation search
- Ecommerce product catalogs
- Content recommendation systems
- RAG (Retrieval Augmented Generation) systems
- Geospatial search applications
- Question answering systems
- Custom observability or cybersecurity search tools
- Much more!
The following topics are covered in this section:
| Topic | Description |
|---|---|
| Get started | Create deployments, connect to Elasticsearch, and run your first searches |
| Ingest data | Options for getting data into Elasticsearch |
| Search approaches | Compare search techniques available in Elasticsearch, including full-text, vector, semantic, and hybrid search |
| Build your queries | Implement your search approaches using specific query languages |
| Ranking and reranking | Control result ordering and relevance |
| RAG | Learn about tools for retrieval augmented generation with Elasticsearch |
| Building applications | Integrate Elasticsearch into your websites or applications |
For an introduction to core Elasticsearch concepts such as indices, documents, and mappings, refer to The Elasticsearch data store.
To dive more deeply into the building blocks of Elasticsearch clusters, including nodes, shards, primaries, and replicas, refer to Distributed architecture.