Elastic named a Leader in the Everest Group Enterprise Search Products PEAK Matrix® Assessment 2026

Elastic has been named a Leader in the Everest Group Enterprise Search Products PEAK Matrix Assessment 2026, holding the largest market share among 16 providers evaluated. The recognition highlights Elastic's unified hybrid search pipeline, deployment flexibility, and open ecosystem, which address enterprise priorities for search accuracy, security, and compliance.

Elastic named a Leader in the Everest Group Enterprise Search Products PEAK Matrix® Assessment 2026 Elastic has been named a Leader in the Everest Group Enterprise Search Products PEAK Matrix® Assessment 2026 and identified as holding the largest market share among all 16 providers evaluated. The Elastic Search AI Platform is a single engine for lexical, semantic, hybrid, and agentic retrieval across structured and unstructured data — built for the governance, deployment flexibility, and open ecosystem that production-scale workloads require. We think this recognition reflects what our customers already know: getting retrieval right at scale and with full security and compliance control is what separates search that works in a demo from search that holds up in production. Why Everest Group recognized Elastic Everest Group's assessment evaluated providers on market impact adoption, portfolio diversity, and value delivered and vision and capability strategy, technology, deployment, commercial model, and support . Elastic was placed in the Leader category and identified as the market share leader across all enterprise search providers assessed. Key strengths cited in the assessment include: Unified hybrid search pipeline: Elasticsearch integrates lexical and vector retrieval, reranking, analytics, and agentic workflows within a single query pipeline, enabling configurable relevance across structured and unstructured enterprise data without separate systems for each retrieval type. ES|QL-based query abstraction: Our query language supports multistage retrieval, filtering, aggregation, reranking, and summarization in a single construct, which reduces the engineering overhead of building complex query orchestration. Deployment flexibility for regulated environments: Elastic supports self-managed, cloud-hosted, and serverless deployments with data locality controls that let compliance-sensitive organizations keep specific data in specific regions or infrastructure — a requirement, not a feature, for financial services, healthcare, and public sector workloads. Integrated observability through Kibana: Query performance, system activity, zero-result tracking, and custom visualizations in one place so that teams can monitor and tune search quality without building separate tooling. Open ecosystem with a free community version: Because Elasticsearch is open source, you own the index format, the schema, and the query logic. The free community version means developers can build and validate before committing to a production deployment. Why this matters for enterprise search buyers Everest Group's buyer research identifies search accuracy and relevance as the top enterprise search procurement priority, followed closely by security and compliance and ecosystem integrations. In our view, Elastic's Leader positioning reflects our ability to address all three: Search accuracy across query types: BM25 for exact matches and dense vector retrieval for semantic queries in the same pipeline and fused with reciprocal rank fusion RRF and reranked before results are returned. There is no tradeoff between keyword precision and semantic relevance. Security and compliance at scale: Role-based access control RBAC , data locality controls, and coverage across SOC 2, ISO 27001, HIPAA, GDPR, and PCI-DSS with permissions enforced at query time, not just at the index level. That distinction matters when you're federating across systems with different access policies. Integrations without the setup tax: Prebuilt connectors, open APIs, and native support for AWS, Azure, and GCP — no custom connector work, schema mapping, or auth wiring for every data source. Scale that holds at production load: Built for the query volumes, concurrent users, and index sizes that expose gaps in platforms that perform well in evaluations but degrade under real workloads. A retrieval foundation for agentic AI: AI agents reason across multiple retrieval steps; one imprecise result early in a chain compounds into a wrong final answer. Elastic's pipeline returns grounded, citation-backed results at consistent latency across every step. What Elastic Search AI Platform delivers The Elastic Search AI Platform gives teams the foundation for enterprise search, retrieval augmented generation RAG pipelines, and agentic AI applications: Hybrid retrieval combining BM25 lexical scoring, dense vector search with native state of the art Jina AI models, and knowledge graph-based retrieval are all resolved in a single query pass. Elasticsearch’s unified vector database helps developers deliver high-precision search and scalable AI experiences faster at lower costs. Elasticsearch Query Language ES|QL for multistage retrieval, aggregation, reranking, and AI-generated summarization are all in one construct. Elastic supports native vector indexing with HNSW for ANN search and DiskBBQ for memory-efficient, large-scale vector workloads. As workloads grow, developers can tune search for latency, recall, and cost-optimizing performance based on their needs using HNSW, DiskBBQ, and quantization, even as they scale to billions. Elastic enables agentic workflow execution within the search pipeline, including multistep query decomposition and action execution. Kibana provides query analytics, search quality monitoring, zero-result tracking, and custom dashboards. Elastic supports self-managed, cloud-hosted, serverless, and hybrid deployments with data locality controls. Elastic provides compliance coverage for SOC 2, ISO 27001, HIPAA, GDPR, and PCI-DSS. Elastic has an open source core with a free community version. Recent momentum Elastic Inference Service EIS : A GPU-accelerated inference layer supporting Elasticsearch semantic search, vector search, and generative AI workflows — compatible with leading large language models LLMs and native multilingual and multimodal Jina AI models. DiskBBQ: A disk-friendly vector search algorithm that applies IVF with BBQ quantization to compress and cluster vectors for selective disk reads. The result is predictable performance on large vector indices without provisioning memory proportional to index size. Elastic Agent Builder GA: Purpose-built tooling for building and deploying AI agents directly within the Elastic platform with support for MCP, A2A, and leading agent frameworks. AWS Agentic AI Specialization: Recognition from AWS for enabling autonomous AI systems using Amazon Bedrock AgentCore and AWS-compatible frameworks for production-ready agentic AI deployment. Organizations across financial services, manufacturing, retail, technology, and the public sector build on Elasticsearch, including deployments that cut legal research time by two days per query and transaction search systems delivering 10x faster query response across 20 years of financial data. Read the full report The Everest Group Enterprise Search Products PEAK Matrix® Assessment 2026 covers all 16 evaluated providers with detailed capability assessments and sourcing guidance. Download the full report https://www.elastic.co/resources/search/report/everest-group-enterprise-search-products-peak . Start a free trial https://cloud.elastic.co/registration or explore Elastic Search AI Platform https://www.elastic.co/enterprise-search to see what production-grade enterprise search looks like. Disclaimer Licensed extracts taken from Everest Group’s PEAK Matrix® Reports may be used by licensed third parties for use in their own marketing and promotional activities and collateral. Selected extracts from Everest Group’s PEAK Matrix® reports do not necessarily provide the full context of our research and analysis. All research and analysis conducted by Everest Group’s analysts and included in Everest Group’s PEAK Matrix® reports is independent and no organization has paid a fee to be featured or to influence their ranking. To access the complete research and to learn more about our methodology, please visit Everest Group PEAK Matrix® Reports .