Elasticsearch

Elasticsearch is a distributed search and analytics engine, a scalable data store and a vector database, tuned for speed and relevance on production-scale workloads. It is the foundation of Elastic's open Stack platform and searches in near real time over very large datasets.

Data is reached through a REST API or one of the official language clients, which keeps it usable from any stack. Elastic publishes its machine learning work and its Lucene contributions through Search Labs, so the engine's direction is visible rather than opaque.

The same engine covers several jobs that are often bought separately.

• Full-text search: relevance ranking over documents at scale.
• Vector search: embeddings stored and queried alongside the rest of your data.
• Retrieval augmented generation: the retrieval half of generative AI applications.
• Observability: logs, metrics and application performance monitoring.
• Security analytics: security logs kept searchable for investigation.

You can create a managed deployment on Elastic Cloud or download and run it yourself. For a laptop, a start-local script brings up Elasticsearch and Kibana in Docker, generates a password and an API key, and writes them to an environment file. That setup leaves transport encryption off and binds to localhost, so it belongs in development only, and its one-month trial of all features reverts afterwards to the free and open Basic tier.