NYSE: ESTC

Our platform is able to ingest data from any source, in any format, and perform search, analysis, and visualization of that data. With Elasticsearch at its core, our platform is a highly scalable document store, columnar database, and search engine and is the unified data store for all of our solutions and use cases. Featuring a common, solution-agnostic user interface with an embedded AI agent and support for third-party AI agents, our platform offers powerful drag-and-drop visual analytics, centralized management capabilities, and the world's most downloaded open source vector database, which gives developers a full suite of sophisticated retrieval algorithms and the ability to integrate with large language models (“LLM”). It delivers the comprehensive set of capabilities developers need to build, maintain, and secure next-generation applications and services. In addition, our out-of-the-box solutions (Elastic Observability and Elastic Security) deliver fast time-to-value for common use cases and, paired with our developer-centric platform which is extensible and customizable, allow us to innovate quickly and differentiate our offerings at every level.

We make our platform available as a service across major cloud providers (consisting of Amazon Web Services (“AWS”), Google Cloud Platform (“GCP”), and Microsoft Azure (“Azure”)) in more than 55 public cloud regions globally. Customers can also deploy our platform across hybrid clouds, public or private clouds, and multi-cloud environments.

Our business model is based primarily on a combination of paid service offerings (Elastic Cloud Hosted and Elastic Cloud Serverless) and free and paid proprietary self-managed software (Elastic Self-Managed). Our paid offerings for our platform are sold via subscription through resource-based pricing, and all customers and users have access to varying levels of features across all solutions. In Elastic Cloud, our family of cloud-based offerings, we offer various subscription tiers tied to different features. For users who download our software, we make some of the features of our software available free of charge, allowing us to engage with a broad community of developers and practitioners and introduce them to the value of our platform.

We believe in the importance of an open software development model, and we develop the majority of our software in public repositories under an open source GNU Affero General Public License v3 (“AGPL”) license, as well as under a proprietary license. Unlike some companies, we do not build an enterprise version that is separate from our free distribution. We maintain a single code base across both our self-managed software and Elastic-hosted services. All of these actions help us build a powerful commercial business model that we believe is optimized for product-driven growth. Elastic has always been committed to open source and an open development process with transparent and direct engagement with our community. The core of Elasticsearch and Kibana (a user interface) are open source under an AGPL license, and our open source code is housed in public repositories.

Our customers often significantly expand their usage of our products and services over time. Expansion includes increasing the number of developers and practitioners using our products, increasing the utilization of our products for a particular use case, and utilizing our products to address new use cases. We focus some of our direct sales efforts on encouraging this type of expansion within our customer base, both within as well as across solutions. Because our business model provides access to all solutions with resource-based pricing, we make it easy for customers to expand across use cases.

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Our business has experienced significant growth around the world. Our total revenue was $1.739 billion, $1.483 billion, and $1.267 billion for the years ended April 30, 2026, 2025, and 2024, respectively, representing year-over-year growth of 17% for the years ended April 30, 2026 and 2025. Subscriptions accounted for 94% of our total revenue for the year ended April 30, 2026 and 93% of our total revenue for the years ended April 30, 2025 and 2024. Revenue from customers located outside the United States accounted for 46%, 44%, and 42% of our total revenue for the years ended April 30, 2026, 2025, and 2024, respectively.

We recorded net income of $367.8 million for the year ended April 30, 2026, net loss of $108.1 million for the year ended April 30, 2025, and net income of $61.7 million for the year ended April 30, 2024. We may incur net losses in the future. Our net cash provided by operating activities was $326.9 million, $266.2 million, and $148.8 million for the years ended April 30, 2026, 2025, and 2024 respectively.

Our Products

Our products enable our customers and users to find relevant information and insights nearly instantly in large amounts of data across a broad range of business and consumer use cases.

Our platform includes a powerful set of solutions able to ingest and store data from any source, in any format, and perform search, analysis, and visualization, usually in milliseconds. Our platform can be used by developers and IT decision makers to power a variety of use cases. We also offer software solutions built on our platform that address a wide variety of use cases. Our platform and each of our solutions (Search & AI, Elastic Observability, and Elastic Security) are designed to run as self-managed software or as a cloud service (in public or private clouds, in hybrid environments, or in multi-cloud environments).

Elasticsearch Platform

At its core, our platform is powered by Elasticsearch—a distributed, real-time vector database and analytics engine and data store for all types of data, including textual, numerical, geospatial, structured, and unstructured. Our platform includes a user interface (known as “Kibana”) that is the visualization layer for data stored in Elasticsearch; this layer is also the management and configuration interface for all parts of our platform.

Elastic has spent years infusing its platform with a strong foundational suite of AI and machine learning capabilities—from support for external machine learning models to native vector search capabilities, supervised and unsupervised machine learning, and solution capabilities that improve search relevance and identify anomalies. Elastic enables organizations by providing the most complete data platform for context engineering and AI. Our commitment to transparency and flexibility ensures that organizations have the visibility and control necessary to integrate AI into workflows with confidence.

Paid features enable capabilities such as automating anomaly detection on time-series data at scale through machine learning, generating embeddings using state-of-the-art models, and performing inference with LLMs. Our platform further facilitates compliance with data security and privacy regulations, supporting search across low-cost cold and frozen data tiers, and allowing real-time notifications and alerts. The source code of features included as part of our platform is generally visible to the public in the form of “open source.”

Our Solutions

We have built a number of solutions into our platform to make it easier for organizations to use our software for common use cases. Our solutions include the following:

•Search & AI. Powered by Elasticsearch, Search & AI includes context engineering and AI, combining a scalable distributed data store, vector database, hybrid search, embedding and reranking AI models, and an agent builder. Elasticsearch simplifies building search, AI, and agentic applications by unifying structured and unstructured data, along with vectors into a single, low-latency engine that delivers precise relevance. Built for production, Elasticsearch scales with near real-time performance and cost efficiency, powering high-throughput ingestion and supporting petabyte-scale datasets.

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•Elastic Observability. Our agentic observability platform brings logs, metrics, and traces into a unified datastore so SRE/Operations teams and AI agents can investigate, correlate, and resolve issues across applications, networks, and infrastructure. Observability includes log analytics, to search, analyze, and visualize petabytes of structured and unstructured logs; infrastructure monitoring, for visibility across cloud, on-premises, Kubernetes, serverless, and hosts; Application Performance Monitoring (“APM”), support for native production-grade OpenTelemetry without proprietary agents and broad language support to pinpoint code issues and debug faster; digital experience monitoring, to improve user experience with synthetic testing and real user monitoring (“RUM”); Streams, which parse and structure raw telemetry data without rebuilding pipelines and Significant Events, which surface critical errors, anomalies, and system changes, cutting time to root cause and giving AI agents the grounded context they need to triage alerts, run investigations, and propose remediations; and LLM observability, to track latency, errors, prompts, responses, usage, and costs across major LLM services and agent frameworks.

•Elastic Security. Elastic Security is an agentic security operations platform where agents handle the full lifecycle from data ingestion through response, and human analysts handle judgment, verification, and approval. Built on the Elasticsearch data and AI platform, it provides unified protection to prevent, detect, and respond to threats. The solution combines Security Information and Event Management (“SIEM”), Extended Detection and Response (“XDR”), endpoint security with third-party integrations and first-party protections, cloud security, and native Security Orchestration, Automation, and Response (“SOAR”) capabilities in a single platform, with integrations across network, host, user, cloud, and endpoint data sources. It enables investigations, incident management, shareable analytics, and workflow automation with AI-driven detection, investigation, and response.

Our Deployment Options

Our platform is available either as self-managed software or a cloud service. With Elastic Self-Managed, users can also download and manage their own deployments of our platform and our solutions. To help with more complex deployment scenarios, we offer paid proprietary products to deliver centralized provisioning, management, and monitoring across multiple deployments. Elastic Cloud, our family of cloud-based offerings (including both Elastic Cloud Hosted and Elastic Cloud Serverless) is hosted on major public cloud providers. We also partner with other cloud providers that offer our software to users on their cloud platform as a hosted offering.

Strengths of our Products

The strengths of our products include the following:

•Speed. Our platform can find matches for search criteria in milliseconds within even the largest structured and unstructured datasets. Its schemaless structure and inverted indices enable real-time search of high volumes of structured, unstructured, and time series data.

•Scale. Our platform is a distributed system and can scale. It has the ability to subdivide search indices into multiple pieces called shards, which enables data volume to be scaled horizontally and operations to be distributed across hundreds of systems or more. A developer running hundreds of nodes has the same user experience as a developer running a single node on a laptop.

•Relevance. Our platform uses multiple analytical techniques, including both traditional and AI-powered relevance techniques, to determine the similarity between stored data and queries, generating highly relevant results reflecting a deep understanding of text and context. Its sophisticated yet developer-friendly query language permits advanced search and analytics. Additionally, the speed of our platform permits query iteration, further enhancing the relevance of search results.

•Ease of Use. Our platform is engineered to take a user from data to dashboard or inquiry to insight in minutes. It offers an easy getting-started experience, featuring streamlined download and deployment, sensible defaults, a simple and intuitive query language, and no need to define a schema up front. Administrative tasks such as securing the platform are intuitive and integrated into the user experience, as are investigative tasks such as data visualization.

•Flexibility. Our platform is able to ingest, filter, store, search, and analyze data in any form, whether structured or unstructured. These capabilities enable our platform to generate insights from a wide variety of data sources for a broad range of use cases. The flexibility of our platform also enables users to begin using our products along with their existing systems, which lowers barriers to adoption.

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•Extensibility. Our platform can be used by developers as a foundation for addressing a wide variety of use cases. Our open approach to building our platform empowers developers to innovate and utilize it to fit their specific needs. Additionally, our developer community actively engages with us to improve and expand our platform.

Our Growth Strategies

We pursue the following growth strategies:

•Extend our product leadership through continued investment in our technology. We continue to invest in our platform, solutions, and services to extend into new use cases, industries, geographies, and customers. We regularly deliver new and enhanced capabilities to our customers, such as the enhanced AI technology integrated in our platform, through regular releases, to which everyone has access based on our subscription model. We continue to offer comprehensive AI capabilities in several key areas, providing organizations with tools and infrastructure to leverage AI, including vector search capabilities, inference and retrieval application programming interfaces (“APIs”), embedding and relevance models, agentic workflows, data ingestion, data management, and domain-specific applications. We view our AI capabilities as a major competitive differentiator for our products and intend to continue to invest in additional features and functionality related to AI. We also offer Elastic Cloud Serverless, a fully-managed, stateless architecture that auto-scales with customer usage. We manage the underlying deployment and customers benefit from automatic upgrades. Our technology investments include foundational platform capabilities as well as solution enhancements for our target use cases.

•Increase product adoption by improving ease of use and growing our user community. With our engineering efforts focused on the user experience, we continue to develop software that makes our products easier to use and adopt for both developers and non-developers. We plan to continue to engage with developers globally to grow our user community through a wide range of touch points such as community meetups, global community groups, hackathons, our global events, our user conferences, which we call ElasticON, and engagement on our website, user forums, and code repositories.

•Expand our customer base by acquiring new customers. We engage our community and our partners to drive awareness and invest in our sales and marketing team to grow our customer base. We offer varied deployment options, including Elastic Self-Managed, Elastic Cloud Hosted, and Elastic Cloud Serverless, to cater to a wide range of customer use cases. Our sales and marketing team conducts campaigns to drive further awareness and adoption within the user community. As a result, many of our sales prospects, including those in executive-level conversations, are already familiar with our technology before entering into a commercial relationship with us. Additionally, we leverage our network of partners to drive awareness and expand our sales and marketing reach to target new customers.

•Expand within our existing customer base through new use cases and larger deployments. We continue to invest in helping users and customers be successful with our products. We view initial success with our products as a path to drive expansion to new use cases and projects and larger deployments within organizations. We often enter an organization through a single use case or solution. Because of the rapid success with our products, knowledge of Elastic often spreads within an organization to new teams of developers, architects, IT operations personnel, security personnel, and senior executives, leading to more use cases for our products and solutions, and larger deployments at higher commitment levels.

•Expand our penetration in enterprise and commercial customer accounts. Using a sales-led motion, we continue to target strategic enterprise and high-propensity commercial customers with our sales teams. We meet our customers where they are, selling Elastic Self-Managed, Elastic Cloud Hosted, and Elastic Cloud Serverless deployments, focusing on high-value existing and new customers.

•Expand our strategic and regional partnerships. We continue to pursue partnerships to further the development of our platform and our customer reach. Our partners assist us in driving awareness of Elastic and our products, using our platform to address customer requirements, and extending our reach in geographic areas and verticals where we do not have a formal sales presence.

•Selectively pursue strategic acquisitions. We intend to continue to pursue acquisitions selectively. Since inception, we have selectively pursued strategic acquisitions to drive product and market expansion. The focus of our most recent acquisitions has been to enhance the technology underlying our Security and Observability offerings.

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Customers

Organizations of all sizes, across many industries, including enterprises, educational institutions and government entities, purchase our products for a variety of use cases. As of April 30, 2026, we had approximately 24,000 customers compared to approximately 21,500 and approximately 21,000 customers as of April 30, 2025 and 2024, respectively. We focus on higher-value customers as exemplified by accounts spending more than $100,000 and $1.0 million annually. As of April 30, 2026, we had more than 1,720 customers spending more than $100,000 annually, and more than 240 customers spending more than $1.0 million annually. One customer, a channel partner, accounted for 11% of total revenue for the years ended April 30, 2026 and 2024, and 12% of total revenue for the year ended April 30, 2025.

Seasonality

We have experienced quarterly fluctuations and seasonality in our sales and results of operations based on our entry into agreements with new and existing customers, customer usage patterns for our consumption-based arrangements, and the mix between annual and monthly contracts entered into in each reporting period. Seasonality in our sales cycle generally reflects a trend toward the highest sales in our fourth fiscal quarter and lowest sales in our first fiscal quarter. We believe this seasonality might become more pronounced as we continue to target large enterprise customers.

Research and Development

We intend to continue to invest in our research and development capabilities to extend our products. Research and development expense totaled $451.9 million, $365.8 million, and $342.0 million for the years ended April 30, 2026, 2025, and 2024, respectively. We plan to continue to devote significant resources to research and development.

Our engineering organization focuses on enhancing existing products and developing new features that are easy to use and can be run in any environment, including in public or private clouds, in hybrid environments, or in multi-cloud environments. With a globally distributed engineering team, we are able to recruit, hire, and retain high-quality, experienced developers, technology leads, and product managers, and operate at a rapid pace to drive product releases, fix bugs, and create new product offerings.

Our software development process is based on iterative releases of our platform. We are organized in small functional teams with a high degree of autonomy and accountability, leveraging AI software development tools to accelerate our time-to-market. Our distributed and highly modular team structure and well-defined software development processes also allow us to successfully incorporate acquired technologies.

Sales and Marketing

We make it easy for users to begin using our products in order to drive rapid adoption. Users can either sign up for a free trial on Elastic Cloud or download our software directly from our website without any sales interaction, and immediately begin using the full set of features. Users can also sign up for Elastic Cloud through public cloud marketplaces.

With our business model, where users can download and use many of our features free of charge, our sales prospects are often already familiar with or using our platform. We conduct low-touch campaigns to keep users and customers engaged once they have begun using our software. This process includes providing high-quality content, documentation, webinars, videos, and blogs through our website. We also drive high-touch engagement with qualified prospects and customers to drive further awareness, adoption, and expansion of our products with paid subscriptions. Many of these customers start with limited initial spending on our products but can significantly increase their spending over time.

Our sales teams are organized primarily by geography and secondarily by customer segments. We rely on inside sales development representatives to qualify leads based on the likelihood they will result in a purchase. We pursue sales opportunities both through our direct sales force and with the assistance of our partners, including through cloud marketplaces. Our relationships within customer organizations often extend beyond the initial users of the technology and include technology and business decision-makers at various levels. We also engage with our customers on an ongoing basis through a customer success team to ensure customer satisfaction and expand their use of our technology.

Partners

We maintain partner relationships that help us market and deliver our products to our customers and complement our community. Our partner relationships include the following:

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•Cloud providers. We work with many of the major cloud providers to increase awareness of our products and make it easy to access our software. We partner with Amazon, Google, and Microsoft to offer Elastic Cloud on AWS, GCP, and Azure, respectively, through direct purchase from us or their respective marketplaces. We also partner with other cloud providers to offer our free and paid proprietary features to users on their cloud platforms.

•Systems integrators, channel partners, and referral partners. We have a global network of systems integrators, channel partners, and referral partner relationships that help deliver our products to business and government customers around the world.

•OEM and MSP partners. Our OEM and MSP partners embed an Elastic subscription into the products or services they offer to their customers. OEM and MSP partners are able to include Elastic’s proprietary features in their product, receive ongoing support from Elastic for product development, and receive support for end customer issues related to Elastic.

•Technology partners. Our technology partners collaborate with Elastic to create a standardized solution for end users that includes technology from both Elastic and the partner. Technology partners represent a deeper collaboration than community contributions and are distinct from distribution-oriented relationships like OEM and MSP partners.

•AI ecosystem. Our AI ecosystem provides customers with a curated, comprehensive set of AI technologies and tools integrated with the Elasticsearch vector database, designed to speed time-to-market, ROI delivery, and innovation. The Elastic AI Ecosystem includes integrations with Anthropic's Claude, Cohere, Confluent, Dataiku, DataRobot, Galileo, Hugging Face, LangChain, LlamaIndex, Mistral AI, NVIDIA, OpenAI, Protect AI, Red Hat, Vectorize.io, and Unstructured, along with all of the major hyperscalers, consisting of AWS, GCP, and Azure.

Services

We offer consulting and training to assist customers in accelerating their success with our software. Our consulting team consists of engineers and architects who bring hands-on experience and deep technical knowledge to a project. Our training offerings enable our users to gain the skills necessary to develop, deploy, and manage our software.

Customer Support

We endeavor to make it easy for users to download, install, deploy, and use our platform and our solutions. Our user community enables users to engage in self-help and collaboration.

However, in many situations, such as those involving complex enterprise IT environments, large deployments, and novel use cases, our users require our support. Accordingly, we include support as part of the subscriptions we sell for our products. Our global support organization consists of engineers who provide technical support services, including troubleshooting, technical audits, cluster tuning, and upgrade assistance. Our support team is globally distributed and provides coverage 24 hours per day, 365 days per year, across multiple languages.

We do not sell support independently and, as such, it is only available for customers who license one or more of our product offerings.

Our Technology

Our platform consists of our three solutions (Search & AI, Elastic Observability, and Elastic Security) and software that supports our various deployment alternatives. Because our solutions are built on top of a common platform, innovations and new capabilities in our platform may benefit many of our solutions. Our customers can customize and extend our solutions to fit their needs by leveraging the power of our platform and our developer capabilities.

Technology Features of the Elasticsearch Platform

Key features of our platform include the following:

•Storage of any type of data. Our platform combines powerful parts of traditional search engines, such as an inverted index to power fast full-text search and a column store for analytics, with native support for a wide range of data types, including text, dates, numbers, geospatial data, date/numeric ranges, and IP addresses. With sensible defaults, and no upfront schema definition necessary, our platform makes it easy to start with simple storage solutions and fine-tune them as datasets grow.

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•Vector database. Elasticsearch is the most downloaded open source vector database, allowing users to create, store, and search vector embeddings at scale. By adding the ability to combine text and vector search for hybrid retrieval—and filtering, ranking, and reranking capabilities to deliver the most relevant results—we go beyond traditional vector databases. Elastic is the only platform with Better Binary Quantization to reduce the memory required without sacrificing accuracy.

•Agent Builder. Elastic Agent Builder is an AI conversational capability that lets you create AI agents that answer questions and take actions over any customer data using natural language. Agents combine LLM reasoning and context engineering with built-in and custom tools that query customer data, so responses are grounded in customer context.

•Machine learning, AI, and alerting. Machine learning capabilities such as anomaly detection, forecasting, and categorization are a tightly integrated part of our platform so as to automatically model the behavior of data, such as trends and periodicity, in real time, to identify issues faster, streamline root cause analysis, and reduce false positives. Without these capabilities, it can be difficult to identify issues such as infrastructure problems or intruders in real time across complex, high-volume, fast-moving datasets. In the last few years, we have also added native support for vector search and model management for advanced machine learning models.

•Powerful query languages. The Elasticsearch query domain specific language is a flexible, expressive search language that exposes a rich set of query capabilities across any kind of data. From simple Boolean operators to custom relevance functions, users can articulate exactly what they are looking for and bring their own definition of relevance. The query language also includes a composable aggregation framework that enables users to summarize, disaggregate, and analyze structured or semi-structured datasets across multiple dimensions. Examples of these capabilities, all with a single search, include tracking the top ten users by expenditure level, looking at data week over week, analyzing data across geographies, and drilling down into details with specific filters.

•Developer centricity. Elasticsearch has consistent, well-documented APIs that work the same way on one node during initial development as on a hundred nodes in production. Elasticsearch also ships with a number of language clients that provide a natural way to integrate with a variety of popular programming frameworks, reducing the learning curve, and leading to a shorter time to realizing value.

•High speed. Everything stored in Elasticsearch is indexed by default, so users do not need to decide in advance what queries they will want to run. Our architecture optimizes throughput, time-to-data availability, and query latency. Elasticsearch can index millions of events per second, and newly added data can be available for search nearly instantly.

•High scale and availability. Elasticsearch is designed to scale horizontally and be resilient to node or hardware failures. As nodes join a cluster, data is automatically rebalanced and queries and indexing are spread across the new nodes seamlessly. This makes it easy to add hardware to increase indexing throughput or improve query throughput. Elasticsearch also detects node failures and hardware or network issues, and automatically protects user data by eliminating the failing or inaccessible nodes and creating new replicas of the data.

•Security. Security features give administrators the rights to grant specific levels of access to their various types of users, such as IT, operations, and application teams. Elasticsearch serves as the central authentication hub for our entire platform. Security features include encrypted communications and encryption-at-rest; role-based access control; single sign-on and authentication; field-level, attribute-level, and document-level security; and audit logging.

Kibana, our platform’s user interface, allows users to manage our platform and to visualize data. Customers can also use Agent Builder’s chat interface to communicate in real time with their data. Additionally, the interfaces for many of our solutions (such as Elastic Observability and Elastic Security) are built into this interface. Key features of our user interface include the following:

•Exploration and visualization of stored data. Our platform’s user interface provides interactive data views, visualizations, and dashboards powered by structured filtering and unstructured search to enable users to get to answers more quickly. Diverse user needs are supported by a variety of data visualization types, such as simple line and bar charts, purpose-built geospatial and time series visualizations, tree diagrams, network diagrams, heatmaps, scatter plots, and histograms.

•Incorporation of advanced analytics and machine learning from Elasticsearch. Our platform’s user interface query, filtering, and data summarization capabilities reflect Elasticsearch’s powerful query domain-specific language and aggregation framework while making it interactive.

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•Management of the Elasticsearch Platform. Our user interface illustrates the health of our platform’s various components and provides timely alerts to notify administrators of any problems. Its central management user interfaces make it easier to operate our platform at scale.

•Home for solutions. Our user interface is where our users and customers access our three solutions: Search & AI, Elastic Observability, and Elastic Security. It provides core services, like security, alerting, and data visualization components, which make it easy for users to discover all of the capabilities our platform and solutions provide.

•Application framework. Our user interface is designed to be extensible. Users interested in a highly specialized visualization type not distributed by default can customize experiences and make these customizations available to the community. Dozens of customizations have been shared by the community via Elastic documentation and code sharing platforms such as GitHub.

Technology Features of our Solutions

Our solutions are designed to minimize time-to-value and deployment costs of using our platform for common use cases. The functionality of our solutions often includes specialized data collection, through standardized APIs or custom agents, and custom user interfaces for specific data analytics, visualizations, workflows, and actions.

Search & AI gives users the tools to improve customer search experiences quickly and scale them seamlessly.

•Search applications. Customers can bring the focused power of our platform to their company website, ecommerce site, workplace search, or applications with sophisticated retrieval algorithms and the ability to integrate with LLMs. Elastic delivers seamless scalability, tunable relevance controls, thorough documentation, well-maintained clients, a refined set of APIs, intuitive dashboards, and robust analytics to build a leading search experience. Customers can build rich applications directly on top of Elasticsearch, or they can use our Application Search framework to rapidly build and customize search applications, including internal workplace search-based experiences.

•Context engineering. Customers use Elasticsearch to build context engines that ground LLMs and AI agents in company-specific information for trustworthy, precise, and cost-efficient outcomes. Elastic unifies enterprise data—structured, unstructured, and vectors—to give LLMs and AI agents the right information at the right time, whether they are powering retrieval-augmented generation pipelines or autonomous workflows. Through Jina AI's multi-modal, multi-lingual embedding models, semantic reranking, and hybrid search across BM25, kNN, and dense vector retrieval, Elastic turns logs, documents, telemetry, and transactions into highly relevant context that AI agents and LLMs can act on with fewer tokens consumed.

Elastic Observability monitors the IT ecosystem of applications, services, and infrastructure to deliver actionable insights into performance and availability.

•Log analytics. Index, search, and analyze structured and unstructured logs at large scale to monitor the health and performance of an organization’s services, infrastructure, and applications. Users can analyze and visualize information extracted from logs to understand system behavior and trends to optimize performance and preemptively address potential issues. By querying logs in ad hoc ways, users can triage, troubleshoot, and resolve performance issues.

•Infrastructure monitoring. With 500+ out-of-the-box integrations and automatic import, users gain visibility across cloud, Kubernetes, serverless, on-premises, and hosts. Intuitive visualizations and quick analysis supported by out-of-the-box machine learning and preconfigured dashboards allow users to troubleshoot faster, as well as measure performance targets for services such as availability, latency, traffic, and errors using service level objectives.

•APM. OpenTelemetry-based APM delivers insights into application performance at the code level. Users can instrument apps and see the lifecycle of a transaction across services from front end to back end. This can give developers confidence in the code they ship, and can give operational teams visibility into code-level errors and performance bottlenecks to accelerate root cause analysis and resolution during an investigation.

•Digital experience monitoring. Customers and users can identify problem areas and improve the overall experiences of their end users as they navigate their digital assets. With synthetic monitoring, customers can track and monitor the availability of the hosts, websites, services, and application endpoints that support business operations. Through proactive monitoring with synthetic monitoring and RUM, customers can detect troublesome components before they are reported by end users.

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•AIOps. Always-on machine learning analysis instantly surfaces anomalies, patterns, correlations, and root causes. AI Assistant and advanced machine learning enable interactive natural language chat experience that integrates with enterprise knowledge bases to quickly resolve issues.

•LLM observability. LLM observability tracks costs, latency, errors, and dependencies of LLMs while ensuring safety and reliability.

Elastic Security delivers unified protection to prevent, detect, and respond to a variety of threats across the IT ecosystem.

•SIEM. Elastic delivers fast, scalable detection and investigation across cloud, network, endpoint, user, and third-party data. Security data is normalized using Elastic Common Schema and enriched to provide relevant context for analysis. Analysts can search across all data, pivot during investigations, and review activity using timeline views and built-in case tracking. AI-assisted features help identify related alerts and prioritize what matters most. The platform is open and accessible, giving teams full control over their data and the flexibility to adapt detections and workflows. Built-in SOAR capabilities streamline response by automating alert forwarding, case creation, and workflow integrations with external tools, thus reducing manual effort without switching platforms.

•XDR. Elastic delivers XDR capabilities by correlating data across endpoints, cloud, network, and user activity, all within the SIEM. Prebuilt rules, machine learning jobs, and AI-driven analytics help detect multi-stage attacks that cross domains. By analyzing native and third-party telemetry together in one interface, Elastic reduces investigation time and eliminates context switching.

•Endpoint security. Elastic Security includes endpoint detection and response capabilities integrated directly into the SIEM. These capabilities detect and block ransomware, fileless attacks, and hands-on-keyboard activity, including on isolated hosts. Endpoint data, whether native or from third-party tools, is analyzed alongside other telemetry to provide context and trigger automated response actions across systems.

•Cloud security. Elastic provides cloud detection and response capabilities directly within the SIEM, giving security teams visibility into activity across multi-cloud environments. These capabilities combine cloud workload monitoring with posture and vulnerability context. Native telemetry from cloud providers and findings from third-party cloud security posture management tools can be ingested and analyzed together, helping teams connect misconfigurations to real-time threats. This unified view across accounts and providers reduces blind spots and speeds up response to risks in modern cloud environments.

•Workflows for security. Elastic Workflows brings native automation directly into Elastic Security, delivering SOAR capabilities without a separate tool. It combines scripted playbooks for defined tasks with AI agents that reason through complex investigations and execute response actions including isolating hosts, querying threat intelligence, and escalating incidents. Workflows for security connects to external systems including Slack, Jira, ServiceNow, and PagerDuty, with representational state transfer (“REST”) API support for additional tools, to coordinate response across the security stack.

Community

Elastic has always been committed to an open development process with transparent and direct engagement with our community. Our team extends beyond our employee base and includes all of the users who download our software. Our users interact with us on our website forums and on X, GitHub, Stack Overflow, Quora, Facebook, and other platforms.

To build products that best meet our users’ needs, we focus on, and invest in, building a strong community. Each download of our platform is a new opportunity to educate our next contributor, hear about a new use case, explore the need for a new feature, or meet a future member of the team. Community is core to our identity, binding our products closely together with our users. Community gives us the ability to get their candid feedback, creating a direct line of communication between our users and the builders of our products across all of our features—including both free and paid capabilities—and enabling us to make our products simpler and better.

The Elastic community has a code of conduct that covers the behaviors of the Elastic community in any forum, mailing list, wiki, website, code repository, Slack channel, private correspondence, or public meeting. It is designed to ensure that the Elastic community is a space where members and users can freely and openly communicate, collaborate, and contribute both ideas and code. This Elastic community code of conduct also covers our community ground rules: be considerate, be patient, be respectful, be nice, communicate effectively, and ask for help when unsure.

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Competition

Our market is highly competitive, quickly evolving, fragmented, and subject to rapid changes in technology, shifting customer needs, and frequent introductions of new offerings. Our principal competitors include:

•For Search & AI: providers of traditional search offerings, such as Algolia, Apache Solr (open source offering), and Coveo; native vector databases, such as Pinecone, Qdrant, and Weaviate; database platforms with integrated vector search, such as MongoDB Atlas; and search tools, such as Google Gemini Enterprise Agent Platform (formerly Vertex AI) and Microsoft Azure AI Search.

•For Elastic Observability: software vendors with specific observability solutions, such as AppDynamics and Splunk (each owned by Cisco Systems), Datadog, Dynatrace, and New Relic.

•For Elastic Security: security vendors, such as Azure Sentinel (owned by Microsoft), CrowdStrike, Google SecOps, Palo Alto Networks, and Splunk (owned by Cisco Systems).

•Certain cloud hosting providers and MSPs, including AWS, which offer products or services based on a forked version of our platform. These offerings are not supported by Elastic and come without any of Elastic’s proprietary features, whether free or paid.

The principal competitive factors for companies in our industry are:

•product capabilities, including speed, scale, and relevance, with which to power search AI experiences;

•an extensible product “stack” that enables developers to build a wide variety of solutions;

•powerful and flexible technology that can manage a broad variety and large volume of data;

•ease of deployment and ease of use;

•ability to address a variety of evolving customer needs and use cases;

•strength and execution of sales and marketing strategies;

•flexible deployment model across public or private clouds, hybrid environments, or multi-cloud environments;

•productized solutions engineered to be rapidly adopted to address specific applications;

•mindshare with developers and IT and security executives;

•adoption of products by many types of users and decision makers (including developers, architects, DevOps personnel, IT professionals, security analysts, and departmental and organizational leaders);

•enterprise-grade technology that is secure and reliable;

•size of customer base and level of user adoption;

•quality of training, consulting, and customer support;

•brand awareness and reputation; and

•low total cost of ownership.

We believe that we compare favorably to our competitors on the basis of the factors listed above. However, compared to us, many of our competitors have substantially greater financial, technical and other resources, greater brand recognition, larger sales forces and marketing budgets, broader distribution networks and presence, more established relationships with current or potential customers and partners, more diverse product and services offerings, and larger and more mature intellectual property portfolios. Our competitors may be able to leverage these resources to gain business in a manner that discourages customers from purchasing our offerings.

We expect that our industry will continue to attract new companies, including smaller emerging companies, which could introduce new offerings. We may also expand into new markets and encounter additional competitors in such markets.

While our products and solutions have various competitors across different use cases, such as search applications and workplace search, logging, metrics, APM, and business and security analytics, we believe that few competitors currently have the capabilities to address our entire range of use cases. We believe our industry requires constant change and innovation, and we plan to continue to evolve search as a foundational technology to solve the problems of today and new emerging problems of the future.

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Intellectual Property

We rely on a combination of patents, patent applications, registered and unregistered trademarks, copyrights, trade secrets, license agreements, confidentiality procedures, non-disclosure agreements with third parties, and other contractual measures to safeguard our core technology and other intellectual property assets. In addition, we maintain a policy requiring our employees, contractors, and consultants to enter into confidentiality and invention assignment agreements. As of April 30, 2026, we had a number of active patents, issued in both the United States and outside of the United States, with expirations ranging from 2030 to 2044. In addition, as of April 30, 2026, we had numerous U.S. and international trademark registrations.

The laws, procedures and restrictions on which we rely may provide only limited protection, and any of our intellectual property rights may be challenged, invalidated, circumvented, infringed, or misappropriated. In addition, the laws of certain countries do not protect proprietary rights to the same extent as the laws of the United States, the Netherlands, or other jurisdictions and, therefore, we may be unable to protect our proprietary technology in certain jurisdictions.

In addition, our technology incorporates software components licensed to the general public under open source software licenses such as the Apache Software License Version 2.0 (“Apache 2.0”) and other permissive licenses. We obtain many components from software developed and released by contributors for independent open source components of our technology. Open source licenses grant licensees broad permissions to use, copy, modify, and redistribute our platform. As a result, open source development and licensing practices can limit the value of our software copyright assets.

For additional information about risks relating to our intellectual property, see the section titled “Risk Factors—Risks Related to our Business and Industry” in Item 1A of this Annual Report on Form 10-K.

Human Capital Management

We believe that our employees (whom we call “Elasticians”) and our culture are vital to Elastic’s long-term success. We support both with human capital management efforts focused on:

•Attracting, engaging, and retaining a talented employee base that values different perspectives, experiences, and backgrounds

•Facilitating strong employee engagement

•Promoting continuous employee learning and development

•Providing a comprehensive total rewards package that seeks to offer fair and consistent pay practices with an emphasis on employee well-being

Our management regularly updates our board of directors and its committees on human capital trends and employee-focused activities and initiatives.

As of April 30, 2026, we had a total of 4,019 employees in over 40 countries globally. None of our U.S. employees are represented by a labor union. In certain countries, we have works councils or follow statutory requirements for employee representation through industry-wide collective bargaining agreements.

Distributed Workforce

Elastic originated as a distributed company and continues to be distributed by design. We have built our processes, systems, and teams so that employees can generally perform their jobs without needing to be physically present at the same location as their colleagues. Just as distributed systems are more resilient, we believe that a distributed workforce helps build a strong company that can scale and adapt as new challenges arise. Our distributed model also expands our reach, broadening our ability to attract talent across regions.

Culture and Values

At the core of our culture is our “Source Code”—a shared set of ideas that guide our approach to business with an emphasis on delivering value for our customers while providing flexibility and balance for our employees, empowering them to be their whole, creative selves.

We endeavor to be an employer of choice and strive to sustain a sense of inclusion and belonging among all employees with programs designed to foster community and an appreciation for the unique experiences and perspectives represented across Elasticians globally. We are committed to ensuring that our employees have a voice and the opportunity to share their ideas and insights through regular employee experience surveys reviewed across multiple organizational levels.

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We support the continuous learning and development of all Elasticians through programs that develop skills for individual contributors, leaders of others, and leaders of the business. We deliver learning and development both through on-demand virtual learning and programs for specific teams or groups of emerging leaders. To promote and reinforce our high standards of ethics and integrity throughout the entire company, we require all employees to acknowledge their compliance with our Code of Business Conduct and Ethics and complete mandatory training on this code, and on whistleblowing, anti-harassment, discrimination, anti-retaliation, and other key policies and standards.

Total Rewards

We aim to provide all our employees with a total rewards package that is market-competitive, emphasizing global consistency and local relevance. We are committed to fair pay without regard to gender, race, or ethnicity. We partner with an external firm to conduct pay equity analysis on a regular basis using established job groupings and control factors to promote appropriate comparisons. We provide benefit programs designed to enable employees to meet their well-being goals, from starting a family to being at their physical and emotional best.

Through our Elastic Cares program, our employees can support the charitable organizations that matter most to them on a local and global level. This program encompasses donation matching, our nonprofit organization program which provides our technology for free to certain nonprofit organizations, and our volunteer time-off initiative.

Government Regulations

Our worldwide business activities are subject to various laws, rules, and regulations of the United States as well as of foreign governments. Our compliance with existing or future governmental regulations, including, but not limited to, those pertaining to global trade, business acquisitions, consumer and data protection, and taxes, could have material impacts on our business. See “