Shay Banon | $1B+
Get in touch with Shay Banon | Shay Banon, the founder and Chief Technology Officer of Elastic, is a defining figure in the evolution of real-time search and data analytics. He created Elasticsearch in 2010, a project that evolved from a personal search tool into a cornerstone of modern data infrastructure. Under his leadership, Elastic has expanded from a specialized search engine into a global platform for observability, cybersecurity, and enterprise intelligence. Banon’s commitment to open-source innovation and his technical vision have made the Elastic Stack a fundamental component for thousands of organizations worldwide. His work remains central to how modern businesses process and understand massive volumes of data in real-time.
Shay Banon is a cofounder and the former CEO of search engine company Elastic, which is based in Mountain View, California.
In January 2022, Banon stepped down as CEO. He is now serving as Chief Technology Officer of Elastic.
Banon helped to develop the search technology that Elastic uses and became CEO of the company in 2017.
An Israeli citizen, Banon received his B.Sc. in Computer Science from Technion, Israel Institute of Technology.
His fortune derives from his nearly 8% stake in the company, which went public in October 2018.
As a founder of Elasticsearch and the CTO of Elastic, I have been fascinated with search ever since I tried to build a recipe app for my wife in 2004, a journey that led to me writing the first few lines of code of Elasticsearch in 2009 and later founding Elastic in 2012. I believe finding beauty and excelling is a combination of perspective and grit. As someone who got into computers by counting the number of job postings in the newspaper, I love building things — a product, a community, or a company — and the process of acquiring the knowledge to do so.
Elastic N.V. is a Dutch-American multinational software company that develops and provides enterprise search, observability, and security solutions powered by its open-source Elastic Stack platform.[1][2]
Founded in 2012 in Amsterdam, Netherlands, by Shay Banon, Uri Boness, Simon Willnauer, and Steven Schuurman—the creators of Elasticsearch and contributors to Apache Lucene—the company originated to commercialize the Elasticsearch search engine, which Banon had open-sourced in 2010.[3][4]
Elastic's core product, the Elastic Stack (also known as ELK Stack), comprises Elasticsearch for distributed search and analytics, Kibana for data visualization and exploration, Beats and Logstash for data ingestion and processing, enabling organizations to collect, analyze, and visualize large volumes of data in real time.[5][6]
The company, legally headquartered in Amsterdam with primary operational headquarters at 88 Kearny Street in San Francisco, California, employs approximately 3,537 people as of April 2025 and serves customers across industries including finance, government, and technology.[7][8]
As a publicly traded entity on the New York Stock Exchange under the ticker symbol ESTC since its 2018 IPO, Elastic reported fiscal 2025 revenue of $1.483 billion, a 17% year-over-year increase, driven by its Elastic Cloud subscription service and AI-enhanced offerings.[9][10]
Elastic's mission is to enable everyone to securely harness search-powered AI to find answers in real time using all their data, emphasizing open-source principles to foster innovation and community collaboration.[9][11]
History
Founding and early development
Elasticsearch, the foundational technology of Elastic N.V., was developed and released as an open-source search engine in February 2010 by Shay Banon.[12] Banon, drawing from his earlier work on the Compass project—a Java-based search framework built on Apache Lucene—aimed to create a more scalable, distributed solution for full-text search and analytics.[13] This initiative addressed limitations in existing tools by emphasizing RESTful APIs, JSON support, and near real-time capabilities, positioning Elasticsearch as a versatile engine for handling large-scale data indexing and querying.[14]
The company behind Elasticsearch was incorporated on February 9, 2012, in Amsterdam, Netherlands, as Elasticsearch B.V., a private limited liability company (besloten vennootschap met beperkte aansprakelijkheid).[15] This Dutch origin aligns with the country's government AI policies, which prefer open-source solutions to promote digital sovereignty; Elastic's core technology, Elasticsearch, being open-source, and its applications in supportive tools like search and analysis rather than high-risk AI systems, fit these preferences.[16][17] It was founded by Shay Banon, Steven Schuurman, Uri Boness, and Simon Willnauer, who brought expertise from prior open-source contributions to projects like Apache Lucene and SpringSource.[18] From its inception, the company focused on expanding Elasticsearch into a broader ecosystem, later known as the Elastic Stack, to support logging, monitoring, and visualization use cases.
In its early years, Elastic prioritized the development and integration of complementary open-source tools. Logstash, an open-source data processing pipeline originally created in 2009, was formally integrated into the ecosystem in 2013, enabling efficient log aggregation and transformation for feeding data into Elasticsearch.[12] Similarly, Kibana, a browser-based visualization dashboard developed by Rashid Khan, was acquired and released under Elastic's umbrella in 2013, completing the initial ELK Stack (Elasticsearch, Logstash, Kibana) for end-to-end data analysis.[12] These releases marked a shift toward a unified platform for observability and search applications.
To fuel growth, Elasticsearch B.V. secured $10 million in Series A funding in November 2012, led by Benchmark Capital, which supported enhancements to its big data search capabilities.[19] Subsequent rounds included a $24 million Series B in February 2013 from Index Ventures, Benchmark Capital, and SV Angel.[20] In June 2014, the company raised $70 million in Series C funding, led by New Enterprise Associates, to accelerate product development and global expansion.[21] Reflecting its evolving product suite beyond search alone, the company rebranded to Elastic N.V. on March 10, 2015, adopting a name that encompassed the full Elastic Stack.[22]
Initial growth and IPO
In 2015, Elastic marked a pivotal phase in its product evolution with the release of Beats 1.0.0 on November 24, which introduced a platform of lightweight data shippers for collecting and shipping logs, metrics, network packets, and other data types to Elasticsearch.[23] This complemented the existing ELK Stack (Elasticsearch, Logstash, Kibana), forming the complete Elastic Stack 1.0 and enabling unified search, logging, and analytics capabilities across diverse data sources. The integration facilitated easier data ingestion and real-time processing, addressing growing demands for scalable observability in enterprise environments.[24]
The maturation of the Elastic Stack drove rapid market adoption between 2016 and 2017, as organizations leveraged it for critical applications in search and monitoring. By 2017, prominent users included Wikipedia, which employed the platform for full-text search across its vast content repository;[25] Netflix, utilizing it for centralized log aggregation and analysis to support streaming reliability;[26] and eBay, applying it for e-commerce site search and performance analytics to enhance user experience.[27] This period also saw substantial venture funding to fuel expansion, including a $58 million Series D round in July 2016 led by Benchmark Capital and NEA, which built on prior investments and positioned Elastic as a unicorn with a valuation surpassing $1 billion ahead of its public debut.[28][29]
Elastic transitioned to a public company with its initial public offering on the New York Stock Exchange under the ticker symbol ESTC on October 5, 2018. The IPO was priced at $36 per share, raising $252 million and valuing the company at approximately $2.5 billion on a fully diluted basis at pricing.[30] Shares surged 94% on the first trading day, closing at $70 and boosting the market capitalization to nearly $4.9 billion. Post-IPO, Elastic accelerated enterprise adoption of its cloud offerings, highlighted by the September 2018 launch of Elastic Cloud Enterprise 2.0, which simplified provisioning, monitoring, and scaling of Elastic Stack deployments in private and hybrid cloud environments for large-scale operations.[31]
Key challenges and expansions
In response to macroeconomic pressures and over-hiring during the post-pandemic recovery, Elastic N.V. reduced its workforce by approximately 13 percent, or nearly 400 employees, in November 2022.[32] This restructuring aimed to streamline operations amid reduced customer spending from small and medium-sized businesses, allowing the company to refocus on core growth areas in search, observability, and security.[33]
Building on its longstanding distributed model, Elastic solidified a remote-first global workforce approach following the COVID-19 pandemic, eliminating the need for a central headquarters and emphasizing flexibility across its international teams.[34] This shift enabled the company to attract talent worldwide without geographic constraints, supporting sustained innovation in a fully remote environment.[35]
At its October 2025 Analyst Day, Elastic raised its fiscal year 2026 revenue guidance to approximately $1.7 billion, reflecting confidence in accelerating AI-driven demand for its platform.[36] Concurrently, the company announced a $500 million share repurchase program, underscoring management's belief in long-term value creation and financial strength.[37]
In 2025, Elastic expanded its AI capabilities with the launch of the Elastic Inference Service (EIS) on October 9, a GPU-accelerated offering integrated into Elastic Cloud to enhance inference performance for vector databases and generative AI workflows.[38] This service simplifies AI application development by providing out-of-the-box support for ingest, investigation, and analysis tasks, reducing deployment complexity for customers.[39] Later that month, on October 30, Elastic integrated its observability tools with Microsoft Azure AI Foundry, delivering real-time monitoring for large language models (LLMs) to track performance, token usage, latency, and costs in agentic AI environments.[40] This partnership enables site reliability engineers and developers to optimize AI agents while ensuring compliance and operational efficiency.[41]
Elastic also published its 2025 Global Threat Report on October 8, analyzing telemetry from over 20,000 customers to highlight the rise of AI-enhanced cyber threats, including malware loaders generated by AI and industrialized browser credential theft.[42] The report emphasizes how adversaries are shifting from stealthy intrusions to high-speed, opportunistic attacks amplified by AI, urging defenders to adopt machine learning-powered detection strategies.[43]
Products and services
Elastic Stack components
The Elastic Stack is a suite of open-source tools designed for search, analytics, and data visualization, enabling organizations to collect, process, store, and analyze data at scale.[44] Its core components—Elasticsearch, Kibana, Logstash, and Beats—work together to form a cohesive system, often referred to as the ELK Stack (Elasticsearch, Logstash, Kibana), particularly for use cases like log analysis where data ingestion, indexing, and visualization are critical.[44] This integration allows for real-time data pipelines that handle diverse data types, from logs and metrics to structured events, supporting distributed environments with high availability and scalability.[44]
Elasticsearch serves as the distributed search and analytics engine at the heart of the Stack, built on Apache Lucene for inverted indexing and full-text search capabilities.[45] It supports real-time indexing of structured, unstructured, numerical, and geospatial data, enabling near real-time searches and complex aggregations such as histograms, metrics, and nested queries via a RESTful API.[45] Architecturally, Elasticsearch operates as a cluster of nodes that distribute data across shards for horizontal scaling, ensuring fault tolerance through replicas and automatic rebalancing.[45] In log analysis scenarios, it indexes incoming events for rapid querying and analysis, allowing users to detect patterns or anomalies across large volumes of data.[44]
Kibana functions as the visualization and exploration interface for data stored in Elasticsearch, providing tools to create interactive dashboards, charts, maps, and reports.[46] It supports querying and filtering data through a browser-based UI, including discover features for ad-hoc exploration and visualization options like lens for drag-and-drop chart building.[46] Basic machine learning capabilities, such as anomaly detection and forecasting, are integrated to model data behavior without requiring separate infrastructure.[46] For log analysis, Kibana enables users to build time-series visualizations of log events, correlating them with metrics for operational insights.[44]
Logstash acts as an open-source data processing pipeline that collects, parses, and enriches logs and events from multiple sources before forwarding them to Elasticsearch or other destinations.[47] Its architecture relies on a plugin-based system with over 200 plugins for inputs (e.g., beats, files, syslog), filters (e.g., grok for parsing, mutate for transforming), and outputs (e.g., Elasticsearch, Kafka).[47] This pipeline supports real-time processing with persistent queues for reliability, ensuring at-least-once delivery and handling ingestion spikes through conditional processing and error handling via dead letter queues.[47] In ELK-based log analysis, Logstash normalizes disparate log formats into a common structure, enriching them with metadata like geolocation or timestamps for consistent indexing in Elasticsearch.[44]
Beats are lightweight, open-source data shippers that run as agents on endpoints to collect and ship operational data directly to Elasticsearch or via Logstash with minimal resource overhead.[48] Written in Go, they feature a small footprint without runtime dependencies, supporting modular collection modules for specific data types.[48] Examples include Filebeat, which tails and forwards log files while preserving line order and adding metadata, and Metricbeat, which gathers system and service metrics like CPU usage or application performance counters at configurable intervals.[48] Other Beats, such as Packetbeat for network data and Winlogbeat for Windows events, extend this to various endpoints.[48] In the Stack's integration model, Beats provide the initial ingestion layer, feeding parsed data into Logstash for further processing or directly into Elasticsearch for indexing, which is then explored via Kibana for comprehensive log analysis workflows.[44]
Cloud and enterprise solutions
Elastic Cloud is Elastic N.V.'s managed Software-as-a-Service (SaaS) platform that enables deployment, scaling, and management of the Elastic Stack components across major cloud providers, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).[49] Available in over 50 regions globally, it handles infrastructure provisioning, security configurations, and automatic scaling to support high-availability workloads without requiring users to manage underlying servers.[50] This service simplifies operations for organizations seeking to leverage Elasticsearch for search, logging, and analytics while ensuring compliance with cloud-specific security standards.[49]
Elastic offers enterprise subscriptions in tiered levels—Platinum and Enterprise—for on-premises and self-managed deployments, which extend beyond the open-source Basic tier by providing premium support, advanced alerting, machine learning features, and graph analytics capabilities.[51] These tiers include 99.95% uptime service level agreements (SLAs) for Platinum and Enterprise subscriptions, along with dedicated support for mission-critical applications.[52] For Elastic Cloud users, these subscription levels integrate seamlessly to unlock additional functionalities like role-based access controls and audit logging, enhancing enterprise-grade security and performance.[51]
Key business applications of Elastic's cloud and enterprise solutions include enterprise search for e-commerce platforms, where it powers site search to deliver personalized product recommendations and improve conversion rates; observability for IT infrastructure monitoring, enabling real-time analysis of logs, metrics, and application performance; and Security Information and Event Management (SIEM) for threat detection and incident response.[53][54] For instance, e-commerce providers use Elastic Enterprise Search to index vast catalogs and provide relevant query results, while financial institutions like Goldman Sachs employ it for scalable data management and observability across global operations.[55]
Pricing for Elastic Cloud follows a consumption-based model, billing users based on resource utilization such as CPU, memory, and storage in Elastic Compute Units (ECUs), with options for pay-as-you-go monthly charges or prepaid commitments.[56] In contrast, on-premises enterprise subscriptions are typically structured as annual contracts tied to node counts and RAM usage, offering predictable costs for large-scale deployments.[51] By fiscal year 2025, Elastic had grown to approximately 21,500 customers, including major enterprises like Microsoft and Goldman Sachs, demonstrating widespread adoption for these scalable solutions.[10][57][55]
AI and security integrations
Elastic Security provides an integrated platform that combines security information and event management (SIEM), extended detection and response (XDR) including endpoint detection and response (EDR), and cloud security capabilities, all enhanced by artificial intelligence (AI) to detect, investigate, and respond to threats.[58] This solution supports proactive threat hunting through advanced querying and behavioral analytics, leveraging machine learning (ML) for anomaly detection to identify unusual patterns in host, network, and user behaviors without requiring predefined rules.[59] For instance, ML-based anomaly detection jobs are preconfigured for SIEM use cases, enabling automated identification of deviations in data streams such as login attempts or file accesses.[59]
In the realm of AI features, Elasticsearch incorporates vector search to enable semantic search, where content is represented as dense vector embeddings to capture meaning beyond keyword matching.[60] This supports retrieval-augmented generation (RAG) workflows by retrieving relevant documents based on semantic similarity, improving accuracy in generative AI applications.[61] Additionally, the Elastic Inference Service (EIS) optimizes inference processes, including GPU-accelerated execution with models like ELSER (Elastic Learned Sparse EncodeR), to deliver fast and scalable semantic search performance.[62]
In 2025, Elastic introduced a new vector storage format designed to enhance efficiency in handling AI embeddings, allowing for optimized storage and querying of high-dimensional vectors in Elasticsearch.[63] Complementing this, LLM observability tools were integrated with Azure AI Foundry, providing metrics and traces to monitor large language model (LLM) performance, costs, and reliability in production environments.[63]
Elastic's offerings align with Dutch government AI policies, which emphasize the use of open-source software and models for transparency and to avoid dependencies on non-EU technologies. As a company founded in Amsterdam with Elasticsearch as its open-source core, Elastic's applications are generally limited to low-risk supportive tools such as search and analysis, supporting digital sovereignty preferences over proprietary US-based solutions. This fits the government's vision, as outlined in its 2025 position paper, and aligns with the Dutch Digitalisation Strategy's prioritization of open source and standards, enabling deployments in sovereign clouds like KPN CloudNL.[16][64][65]
For observability, Elastic's application performance monitoring (APM) integrates AI-driven root cause analysis, using ML to automatically detect anomalies in application traces, metrics, and logs, and correlate them to pinpoint issues like service dependencies or error patterns. In November 2025, Elastic was named a Leader in the IDC MarketScape for Worldwide Observability Platforms and for General-Purpose Knowledge Discovery.[66][67][68] The AI Assistant for Observability further aids this by providing explanations for log messages, assisting with query generation, interpreting stack traces, and suggesting remediation steps through natural language interactions; it focuses on analysis without including automatic code correction.[69]
Elastic's threat intelligence draws from the 2025 Global Threat Report, which highlights how AI is supercharging traditional attacks, including a 15.5% rise in generic threats driven by automated tooling that scales phishing and credential theft.[70] The report emphasizes the industrialization of browser-based threats and the need for AI-enhanced defenses to counter these evolving tactics.[42]
Corporate affairs
Leadership and governance
Elastic N.V. is led by Chief Executive Officer Ashutosh Kulkarni, who has served in the role since January 2022, succeeding co-founder Shay Banon. Kulkarni, previously the company's Chief Product Officer, brings extensive experience from executive positions at McAfee and Informatica, guiding Elastic's strategic expansion in cloud and AI-driven search solutions.[71][72]
Shay Banon, Elastic's co-founder, transitioned to Chief Technology Officer in 2022 after leading as CEO from 2012 to 2022, where he emphasized product innovation rooted in open-source principles. As CTO, Banon continues to oversee technical direction, particularly advancements in the Elastic Stack for real-time data analytics and AI integrations. The executive team also includes Navam Welihinda as Chief Financial Officer, appointed in February 2025 to support accelerated growth and operational efficiency amid the company's AI strategy push; Ken Exner as Chief Product Officer, focusing on product roadmap enhancements; and Joanna Daly as Chief Human Resources Officer, managing talent and culture initiatives.[72][73]
The board of directors comprises eight members, including two executive directors—CEO Ashutosh Kulkarni and CTO Shay Banon—and six non-executive directors, blending founder expertise, investor perspectives, and independent oversight. Key members include Chairman Chetan Puttagunta from Benchmark Capital, co-founder Steven Schuurman, and independents such as Caryn Marooney (former Meta executive), Alison Gleeson (cybersecurity expert), Shelley Leibowitz (former BlackRock executive), and Paul Auvil (finance veteran). This composition ensures balanced decision-making, with committees dedicated to audit, compensation, and nominating/corporate governance to align with shareholder interests.[74][75][76]
Elastic's governance practices prioritize diversity, equity, and inclusion, with board rules mandating consideration of diverse backgrounds in director selection to reflect global perspectives. The company issues annual ESG reports, including FY25 verification of greenhouse gas emissions and progress on science-based targets, alongside enhanced ethics training and data privacy certifications. As a distributed-by-design organization, Elastic maintains a remote-first culture that supports flexible work arrangements, minimizing environmental impact from commuting while fostering global talent acquisition and inclusion.[77][78][79]
Financial performance
Elastic N.V. went public on the New York Stock Exchange in October 2018 under the ticker ESTC, pricing its initial public offering at $36 per share and achieving an initial valuation of approximately $2.5 billion.[80] The company's fiscal year 2019 (ended April 30, 2019) revenue reached $271.7 million, reflecting a 70% increase year-over-year driven by expanding adoption of its Elastic Stack.[81]
The company has sustained strong revenue growth post-IPO, with fiscal year 2025 (ended April 30, 2025) total revenue amounting to $1.483 billion, a 17% year-over-year increase.[10] This included fourth-quarter revenue of $388 million, up 16% from the prior year.[10] In the first quarter of fiscal year 2026 (ended July 31, 2025), revenue rose to $415 million, marking 20% year-over-year growth and exceeding analyst expectations.[82]
Elastic achieved non-GAAP operating profitability starting in fiscal year 2023, with non-GAAP operating income reaching $46 million for the full year at a 4% margin, a milestone reflecting improved operational efficiency.[83] By fiscal year 2025, non-GAAP operating income expanded to $225 million, achieving a 15% margin, while the GAAP net loss narrowed to $108 million through disciplined expense management and revenue diversification.[10]
Revenue composition has shifted toward cloud-based offerings, with Elastic Cloud accounting for 46% of total fiscal year 2025 revenue at $688 million, up from approximately 22% in fiscal year 2020 when Cloud revenue was $92 million out of $428 million total.[10][84] As of early November 2025, Elastic's stock traded around $90 per share, contributing to a market capitalization of approximately $9.4 billion.[85] Looking ahead, the company guided fiscal year 2026 total revenue to between $1.679 billion and $1.689 billion, implying about 14% growth at the midpoint.[82]
Global operations and workforce
Elastic N.V. is incorporated under the laws of the Netherlands, with its registered office in Amsterdam.[86] The company's principal executive offices are located at 88 Kearny Street in San Francisco, California, supporting core operations in search, observability, and security technologies.[87] As a fully distributed organization, Elastic operates across more than 40 countries, enabling a global presence without a single central hub.[86]
The workforce consists of 3,537 employees as of April 30, 2025, reflecting growth following earlier adjustments, including 2022 layoffs that reduced headcount by approximately 13%.[86] Elastic adopted a remote-first policy in 2020, emphasizing flexibility and distributed teams to attract talent worldwide.[79] Key office locations include San Francisco, California, for North American operations, and Amsterdam, Netherlands, for European activities, alongside remote hubs in regions such as Asia and other parts of Europe.[7]
Company culture centers on the open-source community, fostering collaboration through initiatives like the Elastic Stack's development and contributions to projects such as Elasticsearch.[11] Diversity efforts include employee resource groups (ERGs), such as Women of Elastic, which support inclusion and professional growth for underrepresented groups in technology roles.[88][89]
In sustainability, Elastic is committed to reducing greenhouse gas emissions intensity and has submitted science-based targets to the Science Based Targets initiative, with FY25 emissions externally verified, including reductions in emissions intensity despite business expansion.[77]
Acquisitions
Pre-2020 acquisitions
Elastic's pre-2020 acquisitions focused on enhancing its core search and analytics technologies through strategic integrations of complementary startups, primarily between 2015 and 2019. These deals targeted key areas such as cloud hosting, machine learning, site search, and endpoint security, allowing the company to expand the Elastic Stack's capabilities without relying heavily on immediate revenue boosts from the acquired entities.[15]
In March 2015, Elastic acquired Found, a Norwegian-based provider of hosted Elasticsearch services, to bolster its cloud offerings. Found specialized in delivering scalable, managed Elasticsearch solutions for real-time data processing from structured and unstructured sources, serving over 500 customers globally at the time of acquisition. The integration of Found's technology formed the foundation for Elastic Cloud, enabling enterprises to deploy Elasticsearch in public and private clouds with automated management for logging and analytics workloads.[90]
Elastic expanded into machine learning with its September 2016 acquisition of Prelert, a behavioral analytics firm. Prelert's platform provided unsupervised machine learning for anomaly detection in IT infrastructure and application data, embedding real-time analytics directly into the Elastic Stack. This acquisition laid the groundwork for Elastic Machine Learning features, allowing users to identify deviations in data patterns without predefined thresholds, particularly for security and operational monitoring.[91]
In November 2017, Elastic acquired Swiftype, a San Francisco-based startup offering SaaS-based site search solutions. Swiftype, an early adopter of Elasticsearch for indexing and content storage, enabled no-code search implementation for websites and applications, serving enterprise clients with customizable search experiences. The deal enhanced Elastic's enterprise search portfolio by incorporating Swiftype's user-friendly tools into the Elastic Stack, improving relevance and performance for site-specific queries.[92]
Elastic's largest pre-2020 acquisition occurred in June 2019 with Endgame, an endpoint security provider, for a total purchase price of $234 million in cash and stock. Endgame's platform focused on detection and response for endpoint threats using behavioral analytics and threat intelligence, integrating seamlessly with Elasticsearch for unified security operations. This move strengthened the Elastic Security suite by adding endpoint detection capabilities, enabling comprehensive threat hunting across network, cloud, and endpoint data sources.[93][94]
Overall, these acquisitions emphasized talent acquisition and technological synergy over revenue acquisition, aligning with Elastic's strategy of organic innovation in search and analytics during its pre-IPO and early public phases. By prioritizing integrations that extended the Elastic Stack's versatility, the company fostered growth in diverse use cases like observability and security without diluting its open-source roots.[15]
2020s acquisitions
In 2021, Elastic NV pursued an aggressive acquisition strategy to enhance its cybersecurity and observability capabilities, integrating advanced tools for cloud-native environments into its core platform. On September 2, 2021, the company acquired build.security, an Israeli startup specializing in cloud security posture management through policy definition and enforcement using the open-source Open Policy Agent standard. Financial terms were not disclosed, but the acquisition was part of a combined $57.2 million deal with Optimyze. This expanded Elastic's observability offerings by enabling automated compliance and risk assessment for cloud workloads, seamlessly incorporating build.security's technology into Elastic Security for unified threat detection and response.[95][96]
Later that year, on August 25, 2021, Elastic announced the acquisition of Cmd, a Vancouver-based provider of security orchestration, automation, and response (SOAR) solutions leveraging extended Berkeley Packet Filter (eBPF) technology for runtime protection of cloud-native applications. Completed on September 21, 2021, for $77.8 million, the deal strengthened Elastic's extended detection and response (XDR) platform by adding automated incident response workflows, allowing customers to orchestrate security actions across hybrid environments without custom scripting.[97][98][96]
Elastic further advanced its enterprise operations tools with the October 14, 2021, agreement to acquire Optimyze, a Zurich-based developer of continuous profiling software for infrastructure, applications, and services. Finalized on November 2, 2021, for an undisclosed amount (part of the $57.2 million combined with build.security), Optimyze's Prodfiler platform provided always-on performance insights, reducing cloud costs and improving efficiency; it was integrated into Elastic Observability to deliver real-time, low-overhead profiling data alongside logs, metrics, and traces.[99][100][96]
In 2023, Elastic acquired Opster, an Israeli company providing AutoOps and other tools for monitoring and managing Elasticsearch deployments, on November 15, 2023, with completion on November 30, 2023, for approximately $23 million. Opster's platform automates detection and resolution of issues in Elastic environments, enhancing operational efficiency and integrating into Elastic's search operations tools.[101][102][103]
Shifting toward AI-driven enhancements in 2025, Elastic acquired Keep Alerting Ltd., an Israeli open-source AIOps startup, on May 8, 2025, with completion announced on May 21. For an undisclosed sum, Keep's platform unifies alerts from multiple sources, automates incident triage, and applies AI to prioritize operational issues, bolstering Elastic's IT operations management by embedding intelligent alerting directly into the Elastic Stack for faster mean time to resolution (MTTR).[104][105]
Later in 2025, on October 9, 2025, Elastic completed the acquisition of Jina AI, a German-based pioneer in open-source multimodal and multilingual AI models, for an undisclosed amount. Jina AI's embeddings, rerankers, and small language models enhance Elastic's vector search, retrieval-augmented generation (RAG), and context engineering capabilities, making advanced AI search features available via Elastic Cloud.[106]
These 2020s acquisitions, with disclosed amounts exceeding $150 million as of fiscal 2025, focused on cybersecurity, observability, and AI to create a cohesive platform that addresses modern cloud challenges, complementing broader evolutions in Elastic's security integrations.[96][103]
Legal issues
License change controversy
In 2019, Elastic NV began implementing dual licensing for certain components of its Elastic Stack, offering software under both the permissive Apache 2.0 license and its proprietary Elastic License (ELv1) to prevent large cloud providers from offering managed services based on Elastic's technology without contributing to its development or compensating the company.[107] This approach aimed to protect Elastic's research and development investments from commoditization by hyperscalers, who could host and resell the software as a service, capturing value without reciprocity.[108]
The controversy escalated in January 2021 when Elastic announced a significant licensing shift for its core products, Elasticsearch and Kibana, effective from version 7.11 onward. The company relicensed the previously Apache 2.0 code under a dual model of the updated Elastic License 2.0 (ELv2) and the Server Side Public License (SSPL), both of which impose restrictions on offering the software as a hosted service by third parties, particularly targeting hyperscalers like Amazon Web Services (AWS).[109] Elastic justified the change as necessary to sustain innovation, arguing that unrestricted use by cloud giants had eroded its ability to monetize through its own Elastic Cloud offerings, with AWS's Elasticsearch Service cited as a primary example of uncompensated value extraction.[110]
AWS responded swiftly by forking the last Apache 2.0 version of Elasticsearch (7.10.2) and Kibana, launching OpenSearch in April 2021 as a community-driven, open-source alternative under the Apache 2.0 license.[111] This fork, which evolved from AWS's earlier Open Distro project, quickly gained traction, particularly among AWS users, and captured a notable portion of the market for managed search services, with adoption accelerating due to its seamless integration with AWS infrastructure.[112]
The licensing shift sparked intense debate within the open-source community, with critics arguing that SSPL—originally proposed by MongoDB—failed to meet the Open Source Initiative's definition of open source due to its copyleft requirements for cloud providers, effectively making Elasticsearch "source-available" rather than truly open.[113] Proponents, including Elastic's leadership, defended the move as a pragmatic response to unsustainable freeloading by commercial entities, emphasizing that it preserved developer freedom for non-commercial use while safeguarding the company's long-term viability.[112] The controversy highlighted broader tensions in open-source sustainability, influencing similar debates at companies like Redis and MongoDB.
As outcomes, the license change prompted Elastic to accelerate its multi-cloud strategy for Elastic Cloud, diminishing reliance on AWS-hosted deployments and driving internal growth; by fiscal year 2025, Elastic Cloud accounted for 46% of total revenue, up from 43% the prior year, reflecting strengthened direct customer relationships and reduced exposure to third-party commoditization.[10] Meanwhile, OpenSearch's rise fostered competition but also fragmented the ecosystem, leading Elastic to add an OSI-approved open-source option under the AGPLv3 license in 2024 amid evolving market dynamics.[114]
Securities class actions
In February 2025, a securities class action lawsuit was filed against Elastic N.V. in the United States District Court for the Eastern District of New York (Case No. 1:25-cv-00785), alleging violations of the Securities Exchange Act of 1934.[115] The class period spans from May 31, 2024, to August 29, 2024, inclusive, covering investors who purchased Elastic securities during this time and suffered losses due to alleged misrepresentations.[116] Defendants include Elastic N.V., Chief Financial Officer Ashutosh Kulkarni, and President Janesh Moorjani, who are accused of issuing materially false and misleading statements regarding the company's sales operations and financial outlook.[117]
The complaint asserts that defendants failed to disclose significant disruptions in Elastic's sales force stemming from organizational changes implemented in early 2024, which adversely affected sales performance, particularly in the Americas region.[118] These issues led to overstated claims about sales stability, resilience against macroeconomic pressures, and overall growth prospects, including optimistic projections tied to AI-driven demand for Elastic's search and analytics products.[119] The alleged omissions painted an inflated picture of the company's operational health, causing investors to purchase securities at artificially high prices. Multiple law firms, including Robbins LLP, The Rosen Law Firm, and Levi & Korsinsky, have filed notices representing potential lead plaintiffs on behalf of affected shareholders.[119][120][121]
A pivotal event occurred on August 29, 2024, when Elastic announced its first-quarter fiscal 2025 results after market close, reporting revenue of $347 million that exceeded estimates but issuing full-year revenue guidance of $1.44 billion—below prior expectations—due to sales execution challenges and reduced customer commitments.[122] This disclosure, highlighting the impact of sales force instability and softer demand amid economic headwinds, triggered a sharp stock decline of approximately 25% the following day, closing at around $80 per share and erasing significant market value.[123] Investors contend this revelation corrected the prior misleading narrative, leading to substantial losses.
As of November 2025, the litigation remains ongoing, with the lead plaintiff deadline having passed on April 14, 2025. In May 2025, the court appointed Lucid Alternative Fund, LP and Jeff Milan as co-lead plaintiffs. On August 1, 2025, they filed a consolidated amended complaint. No major rulings have been reported.
Disclaimer: This profile is based on publicly available information. No endorsement or affiliation is implied.
Join UHNWI direct Affiliate Program
Earn Passive Income by Sharing Verified Contact Information of Billionaires, Centi-Millionaires, and Multi-Millionaires on the UHNWI Direct Platform
Maximize your earnings potential by sharing direct and validated contact information of the ultra-wealthy, including billionaires, centi-millionaires, and multi-millionaires. Join the UHNWI Direct platform and tap into a lucrative passive income stream by providing valuable data to those seeking high-net-worth connections. Start earning today with UHNWI Direct.
You may also be interested in reviewing other UHNWIs profiles.
To find the person you want to contact, start typing their name or other relevant tags in the search bar.
Please note: Our database contains over 10,000 direct contacts of UHNWIs, and it is highly likely that the individual you are seeking is already included. However, creating individual profiles for each contact is a meticulous and time-intensive process, So, if you are unable to find the profile of the individual you are looking for, please click here.
Filter by Net Worth: All | Billionaires | Centi-Millionaires | Multi-Millionaires
Filter by Location: All | USA | Canada | Europe | UK | Russia & CIS | Asia | MEIA | Australia | Latin America
Filter by Age: 1920-1930 | 1930-1940 | 1940-1950 | 1950-1960 | 1960-1970 | 1970-1980 | 1980-1990 | 1990-2000
Related People
UHNWI direct
