Snapshot

In today’s fast-paced and ever-disrupted markets, the ability to make informed decisions quickly is becoming more and more critical for staying competitive. The key to agility lies in harnessing vast amounts of data to derive actionable insights, drive decision-making and innovation, and transform the way companies operate and succeed.

Elastic is answering these critical business needs, offering a platform that excels in real-time data analytics driven by advanced search capabilities. Elastic specializes in search, observability, and security, providing organizations the tools they need to sift through data efficiently, maintain application performance, and fortify cybersecurity measures. The platform’s power now merges cutting-edge artificial intelligence with the company’s core search technology. While a versatile range of features positions Elastic as a go-to choice for organizations, big or small, seeking strong data analytics tools.

The company serves a diverse client base that spans multiple sectors, including finance, healthcare, and technology. Its use cases are equally varied, encompassing everything from business intelligence and customer experience to IT operations and security monitoring. Elastic engages with a broad developer community to capitalize on product-led growth, which not only targets new customers but also encourages existing ones to expand their usage across different applications and solutions.

The company is in an aggressive growth phase, focused on scaling its business to meet surging demand and capture a greater market share. It is putting particular emphasis on its cloud offerings which continue to be a key growth driver. Simultaneously, it continues to centre on creating user-friendly software to spur product adoption and expand its customer base.

Background

Elastic started from humble beginnings when Shay Banon started with a project called Compass to create a search engine for his wife’s recipes. With the help of fellow founders Steven Schuurman, Uri Boness, and Simon Willnauer in 2012, this evolved into Elasticsearch, which quickly gained attention and set the foundation for Elastic as a search company.

Bolstered by two other open-source projects including Logstash by Jordan Sissel, a tool for ingesting log data, and Kibana by Rashid Khan, a visualization interface, these tools together became known as the ELK Stack: Elasticsearch, Logstash, and Kibana. By 2015, the company changed its name to Elastic to better represent its widening scope. The acquisition of Found, which provided managed Elasticsearch on AWS, consolidated their market offering.

In the years following, multiple product releases including Elastic Cloud, Enterprise, and Workplace Search made it easier for businesses to manage deployments in-house and the rising trend of remote work. While several more acquisitions including Endgame, build.security, and Cmd, broadened the company’s security offerings.

Since going public in 2018, Elastic has continued a rapid expansion and has become a key player in the search and data analytics industry with its growing variety of tools and focus on solving real-world problems.

Leadership

Founder, Shay Banon continues to steer Elastic as the company’s chief technology officer. Banon has been instrumental in directing the company’s technology vision and is a major reason Elastic has become such an influential name in search and data analytics. With a background in computer science, before founding Elastic he worked on other software projects that laid the groundwork for his expertise in search technologies.

Since 2022, Banon has been supported by chief executive officer, Ashutosh Kulkarni. Before that, he was serving as Elastic’s chief product officer. As CEO, he has focused on expanding Elastic’s reach and enhancing its suite of products, especially in the areas of cloud and enterprise solutions. Kulkarni brings with him a wealth of experience in software product management and engineering from his previous senior product leadership and management roles at McAfee, Akamai, Informatica, and Sun Microsystems.

Customer

Elastic offers a comprehensive toolkit for organizations and developers aiming to manage and make the most of their data. Central to these offerings is the Elastic Stack, which consists of Elasticsearch and Kibana. Elasticsearch functions as the engine that powers search and analytics, capable of handling various types of data including textual, numerical, and even geospatial. While Kibana provides the visual front-end, acting as the user interface for all of Elastic’s capabilities. Together, these two core components offer a powerful solution for real-time data search, analysis, and visualization.

Supplementing this core functionality are additional tools including Elastic Agent, Beats, and Logstash, which help with the collection and ingestion of data. Agent monitors logs and metrics, Beats focuses on sending data from edge machines, and Logstash serves as a dynamic pipeline for data ingestion. These components work seamlessly to funnel data from myriad sources into Elasticsearch, setting it up for deeper analysis.

Other paid add-ons that provide further capabilities such as anomaly detection, data security, and real-time notifications allow companies to better meet compliance requirements and enhance their data usage experience. While specialized search, observability, and security solutions help to support mobile apps, customer support systems and internal workplace tools maintain a unified analysis across entire IT ecosystems, and provide a comprehensive approach to organizational cybersecurity.

With versatile deployment options to meet the needs of various organizations, coupled with speed, scalability, and an intuitive user experience, Elastic’s flexibility ensures that businesses of all sizes can effectively utilize the platform. This has led to a broad customer base that includes everything from small businesses and large enterprises to educational institutions and government entities, with more than 20,000 customers across various sectors.

In the real world, e-commerce websites use Elastic for their product search and recommendation features, news organizations rely on it to archive and rapidly search through years of publications, IT teams deploy it to monitor system health and performance, and security firms utilize its extensive defence solutions for comprehensive threat detection and management.

Thematic

Elastic’s growth strategies are underpinned by several key opportunities and approaches to acquire new customers and expand within its existing customer base through new use cases and larger deployments. As users and customers increasingly want to consume highly scalable cloud solutions, the company continues to invest resources in driving further innovation and increasing the adoption of Elastic Cloud in particular. For new customers, this product provides the fastest and easiest way to get started with a free trial, while sales and marketing teams conduct campaigns to drive further awareness and adoption within the user community.

Often entering an organization through a single developer or a small team for an initial project or use case to quickly solve a technical challenge or business problem, knowledge of Elastic frequently spreads to new teams of developers, architects, IT operations and security personnel, along with senior executives. With ease of use a key differentiator, engineering efforts in collaboration with the growing user community, are focused on making products ever easier to use and adopt for both developers and non-developers.

Elastic is capitalizing on two primary trends. The first is Generative AI and its intuitive approach to interacting with massive amounts of information and generating new content, which is driving a resurgence of excitement around enterprise search. Businesses are recognizing the opportunity to create new customer and employee experiences and drive efficiencies in various business processes through the use of AI-powered search. This is opening up new opportunities for Elastic to build generative AI applications that work within an organization’s environment and with its proprietary data. Businesses need the ability to provide accurate context in real-time to large language models. And to do so in a way that does not violate their privacy or security policies. This requires a platform that can allow businesses to use their own or third-party models, irrespective of the type of data.

Built-in AI capabilities such as the Elasticsearch Relevance Engine (ESRE) and the platform’s ability to excel at multiple real-time use cases across search, observability, and security are making Elastic an ideal choice as a core element of their IT stack. In the last quarter alone, the company added several leading customers including a U.S.-based Fortune 100 global media and technology company, a leading file-sharing service, AI platform Labelbox, along with a major telecom equipment company, who are leveraging the platforms for a wide range of distinct use cases that are delivering valuable tangible benefits.

Secondly, Elastic’s platform is encouraging companies to consolidate various workloads, creating a one-stop solution for their needs. The company is securing large multi-year commitments as customers seek ways to lower their total spending without sacrificing innovation by bringing more workloads from other incumbent solutions onto the Elastic platform. Also in the last quarter, this trend has seen deals signed with Texas A&M University, one of the largest multinational communications and entertainment companies, and one of the leading Internet domain registrar and web hosting companies in the world.

On the go-to-market front, Elastic continues to focus on partnerships with the major cloud hyper scalers, as it recently earned top accolades from each of the three incumbents, Microsoft, AWS, and Google Cloud. Deep product integrations with these partners are driving significant growth as customers are making significant multi-year commitments to the platform through these cloud marketplaces.

Financials

Since going public in 2018, Elastic has delivered an impressive run of strong double-digit year-over-year revenue growth without exception. 2023 saw the company exceed a record $1 billion for the first time, as continued adoption of Elastic Cloud resulted in the product’s revenue surging by 42%. The solid trend has continued in the new year as revenue for the first quarter of FY24 rose 17% on the prior year, coming in at $294 million for the period. The strong start and better-than-expected results come as customers continued to consolidate vendors and significant activity around generative AI provided a compelling tailwind.

Elastic operates at a healthy 73% gross profit margin, a solid 50% premium to the sector median. And while the company has been operating at a GAAP loss, at $236.2 million for FY23, a significant portion of operating expenses include stock-based compensation. Consequently, non-GAAP income and margins have been improving most recently, coming in at $29 million and 10% respectively, for the first quarter of FY24, following a result of $46 million and 4% for all of FY23.

Looking ahead, Elastic expects its total revenue for FY24 to be between $1.24 billion and $1.25 billion, growing at 17% compared to last year in line with consensus estimates. The company expects non-GAAP earnings per share to be between $1.01 and $1.11, also in line with consensus expectations at $1.08, representing a surge of 330% over FY23. EPS is then expected to temper to a more modest 30% to 40% growth rate for FY25 and FY26.

Risks/Competition

The market for data analytics and search technology is highly competitive and fast-changing. Elastic faces a variety of competitors, each specializing in different. Major competitors include Solr and Lucidworks Fusion for search, Splunk and New Relic for observability, and CrowdStrike and Azure Sentinel for security. While big cloud providers like AWS offer diverging versions of Elastic’s technology.

Despite stiff competition and many competitors having greater resources, Elastic offers a comprehensive range of solutions for various use cases and its products are designed to be flexible and easy to deploy, allowing for tailored applications, while appealing to a diverse set of decision-makers, from developers to organizational leaders.

Conclusion

Elastic has positioned itself as a vital tool for organizations navigating a now data-driven world. As it continues to break revenue and profitability records thanks to its cutting-edge cloud services and AI capabilities, it looks set for sustained growth and continued market leadership.

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