Elasticsearch
- Company typePublic
- Founded2012
- HeadquartersSan Francisco, United States
- Headcount1,001–5,000
- GTM typeB2B
- OfferingSoftware
Elasticsearch firmographics
Firmographics- Name
- Elasticsearch
- Legal name
- elasticsearch B.V.
- Website
- https://elastic.co
- Company type
- Public
- Founded year
- 2012
- Operating status
- Operating
- Headcount range
- 1,001–5,000 employees
- Ownership category
- akta.pro rank
Elasticsearch industry classification
Industry- Product category
- Enterprise Search and Analytics Platform
- NAICS
- Web Search Portals, Libraries, Archives, and Other Information Services (5192), Web Search Portals and All Other Information Services (519290), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518), Computer Systems Design and Related Services (54151)
- SIC
- Services-Prepackaged Software (7372), Services-Computer Integrated Systems Design (7373), Services-Computer Programming Services (7371)
- akta.pro primary industry
- Enterprise Search, Indexing & Content Discovery (HDAEAGAH)
- akta.pro secondary industries
- Search / Index Databases (HDAEAAAK), Vertical/Specialty Search (e.g., jobs, real estate, travel, products) (BPAMAAAD), AI Search & Generative Engine Optimization (GEO) Services (BPAFAJAO)
Keywords
Where Elasticsearch is headquartered
LocationHeadquarters
- HQ city
- San Francisco
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
Elasticsearch business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Infrastructure, Operations
Revenue model
- Elastic Cloud Subscriptions: Fully managed cloud deployment on AWS, Azure, and Google Cloud with subscription-based pricing including serverless and hosted options. Revenue generated from consumption and capacity-based subscription tiers.
- Self-Managed Software Licenses: Open source core with subscription support for self-managed deployments. Enterprise features require paid subscriptions with tiered support levels (Platinum, Enterprise).
- Support Services: Tiered support offerings (Limited, Base, Enhanced, Premium) with varying response times and coverage. Add-ons available for customized support.
- Professional Services and Consulting: Custom consulting engagements for architecture review, migration planning, and AI strategy consulting.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Subscription | Pay-as-you-go | Elastic Cloud Serverless - Fully managed serverless deployment |
| Subscription | Monthly | Elastic Cloud Hosted - Deploy on AWS, Azure, or Google Cloud |
| Subscription | Annual | Cloud Support - Limited |
| Subscription | Annual | Cloud Support - Base |
| Subscription | Annual | Cloud Support - Enhanced |
| Subscription | Annual | Cloud Support - Premium |
| Subscription | Annual | Self-Managed - Platinum and Enterprise |
Go-to-market motion2 records
Distribution channels8 records
Marketing channels10 records
Elasticsearch product offering
Product offeringCore offering
Elasticsearch is a distributed, RESTful search and analytics engine built on Apache Lucene that stores structured, unstructured, and vector data in real time. The Elastic Search AI Platform combines full-text search, vector search, observability, and security analytics into a unified offering available as self-managed software, fully managed Elastic Cloud (Serverless and Hosted on AWS/Azure/GCP), and on-premises deployments.
Product overview
Elasticsearch is a unified Search AI Platform consisting of the core Elasticsearch distributed search and analytics engine plus multiple integrated modules and deployment options. The platform includes Elasticsearch (the core engine built on Apache Lucene), Kibana (visualization and management interface), and specialized modules including Elasticsearch Vector Database (for semantic and hybrid search), Context Engineering (for AI agent context), Elastic Agent Builder (for building AI agents), Elastic Workflows (native automation), and Jina AI Search Models (multimodal embeddings). Additional modules cover Log Analytics, Cyber Investigation & Incident Response, AutoOps (cluster management), and ES|QL (piped query language). The platform offers flexible deployment via Elastic Cloud Serverless, Elastic Cloud Hosted (on AWS, Azure, Google Cloud), and self-managed options including on-premises and air-gapped environments. Integrations include 450+ data integrations, AI model providers (Jina AI, OpenAI, Anthropic, HuggingFace, LangChain, LlamaIndex), cloud infrastructure, and ecosystem tools (Kubernetes, OpenTelemetry, Prometheus, Slack, PagerDuty, ServiceNow).
Differentiator
Problem solved
Functional benefit
Brands
- Elasticsearch: Open source distributed search and analytics engine built for speed, scale, and AI applications
- Kibana
- Elastic Agent Builder
- Elastic Agent
- Elastic Cloud
- Beats
- Logstash
- Elastic Security
- Elastic Observability
- Elastic Enterprise Search
- AutoOps
- Elastic Workflows
- Jina AI
- Elastic Common Schema (ECS)
- Elastic Inference Service (EIS)
Products and services
- Elasticsearch Open source, distributed search and analytics engine built on Apache Lucene for storing structured, unstructured, and vector data in real time, powering hybrid and vector search, observability, and security analytics.
- Elastic Cloud Serverless Fully managed serverless deployment of Elasticsearch with zero operational load, pay-as-you-go consumption pricing, and 14-day free trial.
- Elastic Cloud Hosted Fully managed Elasticsearch deployment on AWS, Azure, or Google Cloud with monthly subscription billing and ultimate control over scalability.
- Kibana Open source interface to query, analyze, visualize, and manage data stored in Elasticsearch, offering Discover, Dashboards, Canvas, Lens, Maps, alerting, ML, and geospatial analysis.
- Elasticsearch Vector Database
Quantifiable outcome
- Docusign powers millions of e-signature searches daily with Elasticsearch
- +11 more outcomes
Companies that use Elasticsearch
Customer profileNamed customers32 records
Segments1 record
Ideal customer profiles4 records
Elasticsearch technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration30 records
AI capability15 records
Feature10 records
Elasticsearch partnerships and signals
Strategic signalPartnerships
Nine partnerships are on record, tiered core and minor.
- Jina AIcoreJina AI models (embeddings, rerankers, reader) are natively integrated into Elasticsearch through Elastic Inference Service, enabling developers to access Jina AI's top models as part of Elasticsearch's default inference service. Han Xiao serves as VP of AI at Elasticsearch B.V. Partnership shifts search from keyword matching to semantic, multimodal, and AI-native retrieval.
- Amazon Web Services (AWS)coreAWS is a core cloud provider partner for Elastic Cloud deployments. Deploy and scale Elasticsearch on AWS with marketplace integration.
- Microsoft AzurecoreAzure is a core cloud provider partner. Deploy Elasticsearch on Azure with seamless integration and marketplace availability.
- Google CloudcoreGoogle Cloud is a core cloud provider partner for Elastic Cloud deployments with native integration.
- CarahsoftcoreCarahsoft is the US public sector-only distributor for Elastic, serving government agencies and public sector organizations.
- KyndrylminorGlobal system integrator partnership for enterprise transformations and AI adoption initiatives.
- IBMcoreIBM partnership for conversational search combining Elasticsearch with Watsonx Assistant, enabling enterprise AI search solutions.
- Apache LucenecoreElasticsearch is built on Apache Lucene, the underlying search library providing core indexing and search capabilities. Lucene's HNSW algorithm powers vector search in Elasticsearch.
- KubernetescoreElasticsearch runs natively on Kubernetes via Elastic Cloud Kubernetes (ECK) or self-managed deployments with orchestration support.
Scale indicators6 records
Recent moves6 records
Expansion highlights6 records
Elasticsearch competitors and assessment
Company assessmentDirect peers
- Pinecone: Pinecone is a purpose-built managed vector database competing with Elasticsearch's vector database offering for embedding storage and similarity search. Many AI-native developers choose Pinecone over general-purpose platforms like Elastic for RAG and semantic retrieval workloads.
- Splunk: Splunk is the most direct competitor to Elastic in log analytics, observability, and SIEM. Both platforms ingest machine data at petabyte scale, offer search-driven analytics, and compete for the same enterprise security and ops budgets — making them near-substitutes in the largest parts of Elastic's portfolio.
- Dynatrace: Dynatrace is an enterprise observability and security platform competing with Elastic Observability and parts of Elastic Security, particularly for large enterprises needing AI-driven root cause analysis and full-stack monitoring.
- Coveo: Coveo is an enterprise search and relevance platform with strong AI/vector capabilities, competing for the same ecommerce, customer support, and workplace search workloads that Elastic's Enterprise Search targets. Both are positioned as relevance engines for GenAI applications.
- MongoDB: MongoDB Atlas Search combines document database with Lucene-based search, competing with Elastic for search-driven applications and operational analytics. Customers building search-augmented GenAI apps frequently evaluate MongoDB Atlas Vector Search as an alternative to Elasticsearch's vector capabilities.
- Grafana Labs: Grafana Labs competes in observability through LGTM (Loki, Grafana, Tempo, Mimir) stack and offers enterprise-grade logging, metrics, and tracing. It overlaps with Elastic Observability's log analytics and APM, particularly for open-source-leaning enterprises.
- Algolia: Algolia is a developer-focused search-as-a-service platform used for ecommerce, site, and application search. It overlaps directly with Elastic Enterprise Search and Elastic's vector database for customer-facing search use cases, particularly in digital commerce.
- Datadog: Datadog competes head-on with Elastic Observability and increasingly with Elastic Security. Both offer unified infrastructure monitoring, APM, logs, and SIEM/XDR-like capabilities on a SaaS subscription model with similar enterprise customer profiles.
- OpenSearch (AWS): OpenSearch is the open-source fork of Elasticsearch maintained by AWS after Elastic's license change. It is API-compatible with much of the Elasticsearch surface, runs natively on AWS, and is the principal open-source competitor for search, logging, and observability workloads — directly threatening Elastic's developer mindshare.
Broad incumbents
- Microsoft (Azure / Sentinel): Microsoft competes with Elastic across observability and SIEM via Azure Monitor, Microsoft Sentinel, and Copilot for Security. As a hyperscaler with deep enterprise penetration and bundled AI, Microsoft can absorb workloads that would otherwise land with Elastic Security.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks7 records
Key highlights7 records
Customer concentration
Elasticsearch social profiles
Digital presenceElasticsearch compliance and trust
Trust signalCompliance6 records
Elasticsearch financial estimates
Financial estimateRevenue estimate
Valuation estimate
Elasticsearch leadership team
Management profileNumber of profiles
Profiles1 record
Elasticsearch subsidiaries and ownership
Company hierarchySubsidiaries1 record
Elasticsearch funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Elasticsearch M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Elasticsearch
What does Elasticsearch do?
Elasticsearch is a distributed, RESTful search and analytics engine built on Apache Lucene that stores structured, unstructured, and vector data in real time. The Elastic Search AI Platform combines full-text search, vector search, observability, and security analytics into a unified offering available as self-managed software, fully managed Elastic Cloud (Serverless and Hosted on AWS/Azure/GCP), and on-premises deployments.
Is Elasticsearch a public or private company?
Elasticsearch is a public company. It is classified as public and is currently operating.
When was Elasticsearch founded?
Elasticsearch was founded in 2012. It employs 1,001 to 5,000 people.
Where is Elasticsearch based?
Elasticsearch is headquartered in San Francisco, United States, in the North America region.
How does Elasticsearch make money?
Four revenue lines are on record. Elastic Cloud Subscriptions are the primary driver. The others are self-Managed Software Licenses, support Services and professional Services and Consulting.
Who are Elasticsearch's main competitors?
Direct peers on record are Pinecone, Splunk, Dynatrace, Coveo, MongoDB, Grafana Labs, Algolia, Datadog and OpenSearch (AWS). Microsoft (Azure / Sentinel) is listed as a broad incumbent.
Does Elasticsearch have an API?
Yes. Elasticsearch offers a comprehensive RESTful API that enables developers to build search, analytics, and AI applications. The API supports text search, vector search, hybrid search, semantic search, and machine learning capabilities. Language clients are available for Java, Python, Go, Ruby, Rust, .NET, PHP, Perl, and JavaScript. For serverless deployments, specialized clients exist for Go (elasticsearch-serverless-go), Node.js (elasticsearch-serverless-js), Java, Python, Ruby, .NET, and PHP. Developer documentation is at www.elastic.co/docs.
What industry is Elasticsearch in?
Elasticsearch's product category is Enterprise Search and Analytics Platform. Its primary akta.pro industry code is HDAEAGAH, Enterprise Search, Indexing & Content Discovery, with a secondary code of HDAEAAAK, Search / Index Databases. Its NAICS code is 5192 and its SIC code is 7372.