Cloudera Hortonworks Merger: What It May Mean for Big Data Industry

The merger was announced by Cloudera and Hortonworks, two top Big Data vendors. Let’s get into the details about the Cloudera Hortonworks merger.
Cloudera and Hortonworks, big data rivals, announced their mutual agreement to merge in an all-stock merger on October 3, 2018. According to the transaction agreement, Hortonworks stockholders would own 40% of the combined equity, while Cloudera stockholders would have 60%. Hortonworks shareholders will receive 1.305 shares in Cloudera for every 1 Hortonworks share.
The new company will retain the name Cloudera Inc. (CLDR), and Thomas Reilly, the current Cloudera CEO, will continue to hold the position at the combined company. Based on closing prices for these stocks on Wednesday, the deal is estimated to be worth approximately $5.2 billion.
Thomas Reilly describes the merger as “Together With Hortonworks Cloudera allows enterprise data clouds to be delivered from the edge where data originates all the way through to AI getting inside that data.”
“As distinct companies, Cloudera & Hortonworks had a competitive rivalry for nearly a decade. This rivalry helped us become better. We now have a new set, mostly cloud platforms, of competitors. We can grow as a combined company and face these players by being well-positioned in a different market.” – Thomas Reilly.
Highlights from the Cloudera Hortonworks Merger Agreement
Cloudera and Hortonworks have announced a $5.2 billion merger. Let’s take a look at the terms of the transaction agreement for the Cloudera Hortonworks merge:
Establishment of the future leader in data platform with more resources and scale to deliver the industry’s first enterprise data cloud.
New industry standards and a unified platform for customers, partners, community, and AI.
Developing markets and bringing in innovation in IoT and data warehouse, streaming and machine learning, hybrid cloud, AI, and IoT.
Expanding the market opportunities with additional offerings like Cloudera Data Science Workbench or Hortonworks DataFlow.
Partnerships with system integrators, public cloud vendors, and other parties.
Expectations to generate financial benefits and higher margins such as – $720million increase in revenue, 2,500+ clients, 800+ customers above $100,000 ARR and 120+ customers above $1 million ARR. $125 million annual cost synergies. $150 million cash flow in FY20. More than $500 million cash.
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The Merger of Cloudera & Hortonworks: Why?
Let’s now examine the key reasons for the merger and how it may impact big data analysis principles.
Here’s what could have been behind the Cloudera-Hortonworks merger…
Hadoop, an open-source framework, was a favorite tool of big data analytics companies to store data for analysis. Hadoop was synonymous with Big Data. Public cloud platforms like AWS, Microsoft Azure, and others have gained popularity over the years. Their on-premises cloud infrastructure gained popularity. These platforms often included fully integrated Hadoop/Spark services, which are much more affordable than Hadoop distributions such as Cloudera.
Public cloud services also introduced better file systems, which can reduce storage costs for Hadoop storage. BigQuery, a new service that completely eliminates the need for Spark or Hadoop software, is most important.
This led to a significant drop in market share for these distributors, which is expected be the reason for the merger of these distributors i.e. Cloudera and Hortonworks.
Rob Bearden, CEO of Hortonworks, stated that “this compelling merger will create value to our respective stockholders” and that customers, partners and employees will all benefit from the increased offerings, greater scale, and improved cost competitiveness of this combination.
Impact of the Merger Of These Big Data Distributors On Big Data Industry
This merger of these Big Data distributors could have a significant impact on the Big Data market while also competing with public cloud platforms.
The merger can result in a win-win situation for Cloudera customers, partners, and vendors in many ways. Customers will have access the unified platform for big data that provides end-to-end support and more features powered by ML/AI technology. It offers partners solutions that are less expensive and require less effort.