Coveo vs Elastic: pricing, features and which to choose

Coveo is a Canadian software company listed on the Toronto Stock Exchange under the ticker CVO and led by co-founder and CEO Laurent Simoneau. It sells what it calls an AI-Relevance Platform to large enterprises in four areas: commerce search and product discovery, customer service portals and agent tools, websites, and workplace search for employees. Coveo says more than 700 brands use the platform, and its customer announcements include Palo Alto Networks, Intuit, Deloitte, Boston Scientific and the Australian Taxation Office. Commerce was its fastest growing use case in fiscal 2026, at nearly 60% of new business bookings, with strength among B2B manufacturers and distributors.

The core of Coveo is a unified index that pulls content from more than 30 connectors, including Salesforce, ServiceNow, SharePoint, Confluence, SAP Commerce, Shopify and websites, while respecting each source's permissions. Machine learning models rank results by behavior, recommend products and articles, suggest queries and personalize results for each visitor. Merchandisers and administrators get tools to boost, bury or pin results, run A/B tests and read analytics on searches with no results. Coveo offers prebuilt integrations for Salesforce, including Coveo for Agentforce, plus SAP, Adobe and ServiceNow, and headless libraries for teams that build their own front end. Coveo says customers typically go live in four to six weeks.

Coveo's strengths are deep relevance tuning across many content sources, permission-aware indexing, strong commerce merchandising tools, Salesforce and SAP integrations, and generative answers and an MCP server built on the same index. Its weaknesses are quote-only pricing aimed at large budgets, a setup that usually needs partners or internal search specialists, and more platform than a small site needs. Algolia is a developer-friendly hosted search rival. Elastic offers open search infrastructure to build on. Glean focuses on employee workplace search. Google Vertex AI Search covers search and RAG on Google Cloud. Choose Coveo if you run large commerce or support sites and want AI search tuned for revenue.

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.