Prospectus Summary
PROSPECTUS SUMMARY This summary highlights selected information that is presented in greater detail elsewhere in this prospectus. This summary does not contain all of the information you should consider before investing in our common stock. You should read this entire prospectus carefully, including “Risk Factors” and “Management’s Discussion and Analysis of Financial Condition and Results of Operations” and our consolidated financial statements and the related notes included elsewhere in this prospectus, before making an investment decision. Unless the context otherwise requires, the terms “Hortonworks,” “the company,” “we,” “us” and “our” in this prospectus refer to Hortonworks, Inc. and its consolidated subsidiaries.Overview
Our mission is to establish Hadoop as the foundational technology of the modern enterprise data architecture.
We seek to advance the market adoption of Hadoop and provide enterprises with a new data management solution that enables them to harness the power of big data to transform their businesses through more effective and efficient management of their valuable data assets. A Hadoop cluster combines commodity servers with local storage and an open source software distribution to create a reliable distributed compute and storage platform for large data sets scalable up to petabytes, or PBs, with thousands of servers or nodes.
Our solution is an enterprise-grade data management platform built on a unique distribution of Apache Hadoop and powered by YARN, the next generation computing and resource management framework. We continuously drive innovation in the Apache community with a mission to further Hadoop’s development for enterprises of all types and sizes. Our platform deeply integrates with key data center technologies to support best-of-breed data architectures and enables our customers to collect, store, process and analyze increasing amounts of existing and new data types in a way that augments rather than replaces their existing data center infrastructure.
We employ a differentiated approach in that we are committed to serving the Apache Software Foundation open source ecosystem and to sharing all of our product developments with the open source community. We support the community for open source Hadoop, and employ a large number of core committers to the various Enterprise Grade Hadoop projects. We believe that keeping our business model free from architecture design conflicts that could limit the ultimate success of our customers in leveraging the benefits of Hadoop at scale is a significant competitive advantage. We are recognized as a leader in Hadoop by Forrester Research based on the strengths of our current offering and our strategy.
We were founded in 2011, and during 2012 we launched our Enterprise Grade Hadoop platform, the Hortonworks Data Platform for which we provide support subscriptions and professional services. As of September 30, 2014, we had 233 support subscription customers (which we generally define as an entity with an active support subscription) and 292 total customers, including professional services customers, across a broad array of company sizes and industries. We have entered into contracts to establish strategic relationships with Hewlett-Packard Company, Microsoft Corporation, Rackspace Hosting, Inc., Red Hat, Inc., SAP AG, Teradata Corporation and Yahoo! Inc. focused on tightly integrated development, marketing and support strategies to maximize the success of our solutions. Consistent with our open source approach, we generally make the Hortonworks Data Platform available free of charge and derive the predominant amount of our revenue from customer fees from support subscription offerings and professional services.
Index to Financial Statements
We have achieved significant growth in recent periods. For the years ended April 30, 2012 and 2013, our revenue was $1.6 million and $11.0 million, respectively. For the eight months ended December 31, 2012 and 2013, our revenue was $4.8 million and $17.9 million, respectively. For the nine months ended September 30, 2013 and 2014, our revenue was $15.9 million and $33.4 million, respectively. For the twelve months ended September 30, 2014, our revenue was $41.5 million. For the years ended April 30, 2012 and 2013, our gross billings were $11.8 million and $17.6 million, respectively. Effective May 1, 2013, we changed our fiscal year end from April 30 to December 31. For the eight months ended December 31, 2012 and 2013, our gross billings were $9.7 million and $29.1 million, respectively. For the nine months ended September 30, 2013 and 2014, our gross billings were $24.4 million and $53.2 million, respectively. For the twelve months ended September 30, 2014, our gross billings were $65.7 million. See “—Key Metric—Gross Billings” for an explanation of gross billings, a reconciliation of gross billings to total revenue, the most directly comparable GAAP financial measure, and an explanation of why management uses this non-GAAP financial measure. We experienced net losses of $11.5 million and $36.6 million for the years ended April 30, 2012 and 2013, respectively, $19.7 million and $46.2 million for the eight months ended December 31, 2012 and 2013, respectively, $48.4 million and $86.7 million for the nine months ended September 30, 2013 and 2014, respectively, and $101.5 million for the twelve months ended September 30, 2014. See “Selected Consolidated Financial Data—Key Metric – Gross Billings” for more information and a reconciliation of gross billings to total revenue.
Industry Background
Major technology innovations such as social media, mobile and cloud computing, new web-based applications, such as Software-as-a-Service, or SaaS, and the Internet of Things, in which devices with sensors and actuators transmit increasing amounts of data automatically, have created an always-on, constantly connected society that is putting increasing pressure on enterprise data center infrastructure. The increase in volume, velocity and variety of data is creating significant challenges to enterprise data management resources and is disrupting the way enterprises design their data infrastructure.
Enterprises are not only inundated with increasing amounts of data but also struggle with managing more types of data that are less easily managed by traditional data center architectures. Historically, enterprises focused primarily on managing data from dedicated and disparate data center systems and were able to utilize relational database management systems optimized for analyzing preselected, structured data stored within isolated silos.
The variety of data, including new unstructured data types such as clickstream data, geo-location data, sensor and machine data, sentiment data, server log data and other data generated by emails, documents and other file types, is fueling the exponential growth in the aggregate amount of data that has the potential to be captured and managed by the enterprise to drive business value. The higher volume, velocity and variety of context-rich data have historically not been captured, managed or analyzed by the enterprise.
As a result of the limitations of traditional data center architectures, enterprises are seeking new technologies to collect, store and access this data in a cost-effective manner, and to gain more actionable insight from their increasingly complex and growing data stores. Enterprises need to upgrade their data center architectures to enable themselves to bring large volumes of data under management and to process and analyze multiple types of data in innovative ways.
Hadoop was originally developed in the early 2000s. Partnering with the Apache Hadoop community, Yahoo! led major innovations in the technology to help tackle big data challenges and operate its business at scale. The traditional Hadoop offering (i.e., Hadoop Version 1.x) is largely a batch system that enables users to manage data at scale, but requires siloed computing clusters by
Index to Financial Statements
application with pre-selected data sets, thus limiting accessibility, interoperability and overall value. Incremental attempts to improve traditional Hadoop focused on bolting on data warehousing and analytics functionality as well as basic levels of security and operations management. This innovation demonstrated the early promise of Hadoop in enabling enterprises to address their big data requirements, but traditional Hadoop still lacks the breadth of functionality and resiliency that would enable it to be deployed more broadly by enterprises in production use cases.
To improve on this early functionality, Hortonworks engineers created the initial architecture for YARN and developed the technology for it within the Apache Hadoop community, leading to the release of YARN in October 2013. This technology advancement transformed Hadoop (i.e., Hadoop Version 2.x) into a platform that allows for multiple ways of interacting with data, including interactive structured query language, or SQL, processing, real-time processing and online data processing, along with its traditional batch data processing. YARN eliminates the need to silo data sets and enables a single cluster to store a wide range of shared data sets on which mixed workloads can simultaneously process with predictable service levels. YARN is designed to serve as a common data operating system that enables the Hadoop ecosystem to natively integrate applications and leverage existing technologies and skills while extending consistent security, governance and operations across the platform. With these capabilities, YARN can facilitate mainstream Hadoop adoption by enterprises of all types and sizes for production use cases at scale.
Our Opportunity
Enterprises are facing an increasing need to adopt big data strategies that will help them modernize their data center architectures, control costs and transform their businesses to succeed in an increasingly digital world. Inherent in this shift is a move from the post-transaction, reactive analysis of subsets of data to a new model of pre-transaction, interactive insights across a comprehensive and integrated dataset. We believe that enterprises that successfully adopt a big data strategy will succeed, whereas enterprises that fail to implement a modern data architecture will struggle to sustain competitive advantages.
We believe that an enterprise-grade Hadoop solution must meet certain requirements to create and accelerate widespread market adoption and enable the modern data center architecture. We refer to this set of requirements as Enterprise Grade Hadoop, and believe they include:
We believe that only with a platform that addresses each of these needs will enterprises be able to transform their businesses by adopting a modern data architecture that solves their increasing data management requirements. Enterprise Grade Hadoop is fundamental to this architectural shift and can turn what was traditionally viewed as a cost center into a revenue generator by enabling new business applications that harness the power of big data. According to Allied Market Research, the global Hadoop market spanning hardware, software and services is expected to grow from $2.0 billion in 2013 to $50.2 billion by 2020, representing a compound annual growth rate, or CAGR, of 58%.
Index to Financial Statements
Our Solution
We are a leading provider and distributor of an enterprise-grade Hadoop solution that is enabling a re-platforming of data center architectures to harness the power of big data for the enterprise. We provide support subscription offerings and related professional services around the Hortonworks Data Platform, which is our open source software distribution of Apache Hadoop. We developed the Hortonworks Data Platform to address the limitations of traditional Hadoop. The Hortonworks Data Platform provides the following benefits:
We are committed to serving the Apache Software Foundation open source ecosystem and to sharing all of our product developments with the open source community. We support the community for open source Hadoop, and employ a large number of core committers to the various Enterprise
Index to Financial Statements
Grade Hadoop projects. This commitment allows us to drive the innovation of Hadoop’s core open source technology, define a roadmap for the future, ensure predictable and reliable enterprise quality releases and provide comprehensive, enterprise-class support.
Our Strategy
We intend to grow our business by focusing on the following strategies:
Risks Affecting Us
Our business is subject to numerous risks and uncertainties, including those highlighted in “Risk Factors” immediately following this prospectus summary. These risks include, but are not limited to, the following:
Index to Financial Statements
not successful in maintaining and expanding the compatibility of the Hortonworks Data Platform with such products and services, our business will suffer.
Corporate Information
We were incorporated in Delaware in April 2011. Our principal executive offices are located at 3460 W. Bayshore Road, Palo Alto, California 94303, and our telephone number is (408) 916-4121. Our website address is www.hortonworks.com. Information contained on or that can be accessed through our website does not constitute part of this prospectus and inclusions of our website address in this prospectus are inactive textual references only.
“Hortonworks” is our registered trademark in the United States and in certain other jurisdictions. “Hadoop” is a registered trademark of the Apache Software Foundation. Other trademarks and trade names referred to in this prospectus are the property of their respective owners.
Implications of Being an Emerging Growth Company
As a company with less than $1.0 billion in revenue during our last fiscal year, we qualify as an “emerging growth company” as defined in the Jumpstart Our Business Startups Act of 2012, or the JOBS Act. An emerging growth company may take advantage of specified reduced reporting requirements that are otherwise applicable generally to public companies. These provisions include:
We will remain an emerging growth company until the earliest to occur of: the last day of the fiscal year in which we have more than $1.0 billion in annual revenue; the date we qualify as a “large accelerated filer,” with at least $700 million of equity securities held by non-affiliates; the issuance, in any three-year period, by us of more than $1.0 billion in non-convertible debt securities; and the last day of the fiscal year ending after the fifth anniversary of this offering. We may choose to take advantage of some, but not all, of the available benefits under the JOBS Act. We are choosing to irrevocably “opt out” of the extended transition periods available under the JOBS Act for complying with new or revised accounting standards, but we intend to take advantage of the other exemptions discussed above. Accordingly, the information contained herein may be different than the information you receive from other public companies in which you hold stock.