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Data Infrastructure

Elastic

Search and analytics platform behind Elasticsearch, with vector search

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About Elastic

Elastic develops Elasticsearch, a distributed search and analytics engine, along with Kibana and solutions for search, observability and security. It supports vector search and retrieval for generative AI applications and is offered as Elastic Cloud or self-managed software. The company is publicly listed.

Common use cases

  • RAG applications
  • Enterprise search
  • Log and observability data
  • Security analytics

Social listening

What people are saying about Elastic

Reviewers value search speed, scale and Kibana, and buyers typically plan for pricing, documentation, tuning and licensing scope.

What stands out

  • Fast search results and handling of large volumes.
  • Kibana is a strong option for dashboards and monitoring.
  • Connects readily with third-party tools and cloud storage.
  • Self-hosted or managed options help manage cost.

Things to consider

  • Worth modeling pricing, including storage, early on.
  • Ask about documentation and support for customized needs.
  • Plan performance testing for very large scale and frequent updates.
  • Teams typically budget time to learn the query language for advanced queries.
Sources (1)

Themes summarized from public reviews, community discussion and press coverage as of November 2026. They reflect public discussion, not a rating or an endorsement by AI Connect.

Products and services

Elasticsearch

Distributed search, analytics and vector database.

Kibana

Visualization and exploration interface.

Elastic Cloud

Managed service on major clouds.

Elastic Observability and Security

Solutions built on the same data platform.

Key features

  • Full-text search
  • Vector search
  • Hybrid retrieval
  • Log analytics
  • Machine learning
  • Role-based security

Integrations

  • AWS
  • Google Cloud
  • Microsoft Azure
  • OpenAI
  • LangChain
  • Kafka
  • Logstash

Elastic alternatives

FAQs

Is it open source?

Elasticsearch is available under open source licensing options, with commercial features in paid tiers.

Can it do RAG?

Yes, it supports vector and hybrid search for retrieval.

How is it deployed?

As Elastic Cloud or self-managed.

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