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Elastic named a Leader in The Forrester Wave™: Cognitive Search Platforms, Q4 2025

By

Natalie Blake

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Today, we’re excited to share that Elastic has been named a Leader in The Forrester Wave™: Cognitive Search Platforms, Q4 2025. We believe this recognizes our continued innovation in AI-powered search and the momentum of the Elasticsearch Platform. 

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Why Forrester recognized Elastic

In its evaluation, Forrester noted: “Elastic’s core search offering, Elasticsearch, forms the basis of Elastic’s Search AI Platform, combining with Elastic’s Logstash and Kibana. Together, they enable a wide range of search-driven use cases supported by strong observability and compliance.” Elastic aims to enable enterprises to retrieve insights from every type of data, structured and unstructured, with a cognitive search platform that is highly customizable and extensible as well as user-friendly.

Our placement as a Leader reflects Elastic’s commitment to continued innovation in search, data storage, and applied AI packaged in the most downloaded, distributed open source AI platform for modern builders. Key strengths include:

  • Depth of relevance and results delivery: The Forrester report states, “Elastic’s outstanding capabilities in enabling deep and comprehensive refinement of relevancy and results delivery let developers push their imaginations in terms of building search experiences.”

  • Scalable, efficient, and flexible deployment: Elasticsearch is the world’s most widely deployed vector database built to store and search both dense and sparse vectors and scale to billions of documents. This scalability and efficiency is paired with a varied set of hosting options — cloud, serverless, and on-prem — making the platform flexible in both technology and deployment.

  • Customizable, extensible developer experience: Elasticsearch is highly customizable, scales for all types of unstructured and structured data, and is easily extensible for different search experiences. Forrester notes that the market welcomed Elastic’s return to an open source model for its platform, which has the potential to speed its innovation and iteration of customer-centric capabilities via a deeper relationship with the developer community.

  • Roadmap aligned to modern AI search: The Forrester report also cites the introduction of Elasticsearch Query Language (ES|QL) and more granular controls for vectorization and large language model (LLM) inferencing, empowering developers to build next-gen search and generative AI (GenAI) experiences. For hands-on walkthroughs of these capabilities, see Elasticsearch Labs.

  • Customer feedback: Customers describe Elastic as a comprehensive and technically mature platform, with flexibility to deploy across environments and scale effectively.

Forrester’s take: Elastic is a great choice for companies that want to build a scalable search experience and customize in terms of experiences, apps, and deployment patterns.

Why this matters for customers

Modern teams need more than a vector store and an LLM. They also need highly performant and accurate retrieval of context with limitless scale to engineer the needs of real-time analytics and workflow intelligence automation. Elastic is trusted globally to store distributed data securely, observe and monitor, and provide the right answers to human-driven search or AI agents. 

What’s new and what’s next in Elasticsearch and generative AI

  • ES|QL for everyone — faster investigations, simpler pipelines: ES|QL brings a piped, composable query language to search and analytics, so that developers and practitioners can filter, transform, enrich, and analyze data quickly. It now includes expanding capabilities for scale, joins, and cross-cluster queries.

  • Production-grade vector and hybrid retrieval: Elastic keeps advancing vector search to power semantic and retrieval augmented generation (RAG) use cases:

    • Multiple similarity options (e.g., cosine, dot product, and max inner product) to fit different embedding models

    • Improvements in indexing and recall plus support for larger dimensional embeddings — all designed for low-latency, high-quality results in production

  • The retrieval engine for GenAI apps: Elasticsearch gives teams the building blocks for AI search, such as hybrid retrieval, model integration, orchestration hooks for LLMs, and tooling to tune relevance, so you can stand up RAG and agentic patterns without stitching together point tools.

  • Serverless elasticity for search and GenAI: With Elastic Cloud Serverless, teams can spin up optimized search and GenAI projects in minutes, scale automatically, and tap into a rich vector and API ecosystem — ideal for pilots that need a clear path to production.
  • Built-in AI assistants where you work: Elastic AI Assistant helps site reliability engineers (SREs) and analysts ask questions in natural language, draft queries like ES|QL, interpret results, and accelerate troubleshooting — bringing GenAI directly to observability and security workflows.

What customers can do with Elastic today

  • Launch grounded GenAI: Use Elasticsearch vector database to feed LLMs accurate, fresh context from your own data for RAG and answer generation and conversational experiences.

  • Upgrade relevance: Blend keyword precision with vector semantics, metadata filters, and ranking controls to deliver consumer-grade search in enterprise apps. 

  • Ship faster with serverless: Start small, scale on demand, and avoid undifferentiated infrastructure while keeping enterprise-grade security and governance. 

  • Boost productivity: Let AI assistants draft queries, summarize results, and guide next steps within Elastic.

Thank you to our community and customers

For us, this recognition reflects the work of our customers, developers, and open community who continue to push what is possible with search and AI. We are doubling down on a platform that is open, flexible, and fast, so you can turn data into action safely and at scale.

Read the full report

The Forrester Wave™: Cognitive Search Platforms, Q4 2025 is now available. Read the report.

Forrester does not endorse any company, product, brand, or service included in its research publications and does not advise any person to select the products or services of any company or brand based on the ratings included in such publications. Information is based on the best available resources. Opinions reflect judgment at the time and are subject to change. For more information, read about Forrester’s objectivity here.

The release and timing of any features or functionality described in this post remain at Elastic's sole discretion. Any features or functionality not currently available may not be delivered on time or at all.
In this blog post, we may have used or referred to third party generative AI tools, which are owned and operated by their respective owners. Elastic does not have any control over the third party tools and we have no responsibility or liability for their content, operation or use, nor for any loss or damage that may arise from your use of such tools. Please exercise caution when using AI tools with personal, sensitive or confidential information. Any data you submit may be used for AI training or other purposes. There is no guarantee that information you provide will be kept secure or confidential. You should familiarize yourself with the privacy practices and terms of use of any generative AI tools prior to use. 
Elastic, Elasticsearch, and associated marks are trademarks, logos or registered trademarks of Elasticsearch N.V. in the United States and other countries. All other company and product names are trademarks, logos or registered trademarks of their respective owners.

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