Elastic vs Glean: pricing, features and which to choose

Elastic is a public company that builds Elasticsearch, a distributed search and analytics engine first released in 2010, along with Kibana for dashboards and data exploration. Developers use it for website and app search, log analytics, observability, security analytics and, increasingly, as a vector database for retrieval augmented generation. In 2021 Elastic moved Elasticsearch and Kibana from Apache 2.0 to the Elastic License and SSPL, and in 2024 it added the OSI-approved AGPLv3 as a third option, so Elastic now describes the code as open source again. It runs on Elastic Cloud on AWS, Google Cloud and Azure, or self-managed on premises and in Kubernetes.

For search, Elasticsearch combines classic keyword ranking with dense and sparse vector search, so teams can run hybrid queries, rerank results and filter by metadata in one engine. Elastic's own ELSER model produces sparse embeddings, and since acquiring Jina AI it offers Jina embedding and reranking models. ES|QL is a piped query language for search and analytics. Playground lets developers test RAG against their indexes with different LLMs, and connectors pull content from sources such as SharePoint, Confluence, Google Drive and databases. Elastic Observability and Elastic Security build on the same data store, with AI assistants for investigating incidents and alerts.

Elastic's strengths are a proven search engine at huge scale, hybrid keyword and vector search in one system, an open source option, deployment anywhere, and Agent Builder with built-in MCP for agent access. Its weaknesses are operational complexity when self-managing, pricing models with many dimensions that take time to estimate, and a steep learning curve for query tuning. OpenSearch is the Apache-licensed fork led by AWS. Pinecone and Qdrant are dedicated vector databases. Algolia is a hosted search API with simpler setup. Coveo sells enterprise search with generative answers, and Snowflake Cortex and Databricks add AI search inside data warehouses. Choose Elastic if you want one engine for search, analytics and AI retrieval.

Glean is an enterprise AI company founded in 2019. Its product connects workplace information to search and assistant workflows. Unlike a standalone consumer chatbot, its value depends on integration with the organization's documents, applications, identities, and access permissions.

Deployment begins with connecting business systems and configuring identity and permissions. Employees can then search across connected information or ask questions grounded in organizational content. Agent workflows build on that foundation, making connector coverage and permission configuration part of the buying decision.

Glean competes with Guru for organizational knowledge access, Microsoft 365 Copilot for suite-centered assistance, and Atlassian Rovo for connected workplace search. Its trade-off is enterprise deployment and negotiated pricing rather than a self-serve trial price. Pick Glean when cross-application knowledge access and permissions justify an organization-wide implementation.