Global Hadoop Market Research Report 2024-Competitive Analysis, Status and Outlook by Type, Downstream Industry, and Geography, Forecast to 2030

Global Hadoop Market Research Report 2024-Competitive Analysis, Status and Outlook by Type, Downstream Industry, and Geography, Forecast to 2030

Hadoop, formally known as Apache Hadoop, was developed as part of an open source project within the Apache Software Foundation. Hadoop is a Java-based open source framework for storing and processing big data. Data is stored on inexpensive commodity servers running as a cluster. Its distributed file system supports concurrent processing and fault tolerance. Hadoop is the center of the big data technology ecosystem and is primarily used to support data science and advanced analytics initiatives, including predictive analytics, data mining, machine learning, and deep learning. Facebook, Yahoo, Google, Twitter, LinkedIn, and more are using it.

Market Overview:

The latest research study on the global Hadoop market finds that the global Hadoop market reached a value of USD 3772.68 million in 2023. It’s expected that the market will achieve USD 5923.52 million by 2029, exhibiting a CAGR of 7.81% during the forecast period.

Like many industries, the Hadoop market has experienced disruption during the COVID-19 pandemic. The crisis has affected IT infrastructure, slowed down hardware supply chains and reduced manufacturing activity. Open source contributors have responded quickly to the pandemic, with more than 10,000 people estimated to have contributed to numerous open source projects. Governments are also developing new open source tools to combat COVID-19. For example, contact tracing apps have been downloaded by millions in countries such as Italy, Singapore, and India. Hadoop, an open source software framework for distributed storage and processing of large data sets, is a valuable tool in the fight against COVID-19. In response to the COVID-19 pandemic, many government and non-governmental organizations are providing COVID-19 datasets while using the Hadoop framework and ecosystem for data analysis and providing information on the number of cases, tests completed, and healthcare such as beds, medicines, etc. As hospitals and medical institutions around the world generate large amounts of data, traditional data processing methods may no longer be sufficient. Hadoop's distributed processing capabilities allow medical researchers to quickly process and analyze large amounts of data to understand the behavior and impact of the virus more quickly and accurately. Hadoop is also used in contact tracing efforts. By analyzing large data sets of patient and contact information, Hadoop helps identify and isolate individuals who may have been exposed to the virus, limit its spread, and help keep communities safe. Another application of Hadoop is in the development of treatments and vaccines. Hadoop's ability to process and store large data sets helps researchers analyze medical data more efficiently, thereby speeding up the development and approval of treatments and vaccines.

Advantages of Hadoop

Hadoop has many advantages. Hadoop is an open source software based on Java applications and therefore compatible with all platforms. This means that anyone with programming knowledge and storage space can create a Hadoop system. Allow more employees to access Hadoop without requiring a license. Hadoop uses open source technology on cheap cloud servers to manage, access, and process large data stores. It provides significant cost savings compared to many proprietary database models. Hadoop owes its success largely to a processing framework called MapReduce that is at the core of its existence. MapReduce technology provides opportunities for all programmers. Programmers do not need to understand high-performance computing to work efficiently without having to worry about the complexity within the cluster, task monitoring, node failure management, etc. Hadoop also contributes another platform, the Hadoop Distributed File System (HDFS). The main advantage of HDFS is its ability to scale quickly and work smoothly regardless of any node failures. Hadoop's distributed file system, concurrent processing, and MapReduce models can run complex queries in seconds, significantly increasing processing speeds. It can process terabytes of data in minutes and petabytes of data in hours. Hadoop has a high level of fault tolerance because data stored in any particular node is also replicated elsewhere in the cluster. Cloud installations of Hadoop are also particularly well-suited to its distributed file system. Users can easily scale the system to handle more data simply by adding nodes. The Hadoop system can handle various forms of structured, semi-structured, and unstructured data, providing users with greater flexibility than relational databases and data warehouses to collect, manage, and analyze data. Includes transaction data, Internet clickstream records, web server and mobile application logs, social media posts, customer emails, sensor data from the Internet of Things, and more. It can support real-time analytics applications to help drive better operational decisions, as well as batch workloads for historical analysis. These capabilities helped Hadoop become the foundational data management platform for big data analytics purposes after its emergence in the mid-2000s. Thus, Hadoop enables organizations to collect, store, and analyze more data. Hadoop architecture is popular in the big data market due to its wide usability and application scope and being a cost-effective solution.

Increasing business competition has generated a large amount of unstructured data

Data can be roughly divided into structured data and unstructured data. Structured data can be defined as data that can be stored in a relational database. Unstructured data is information that lacks a predefined data model or is not organized in a predefined way. Unstructured data can include conversations via email or text messages but also includes social media posts, blogs, videos, audio, call logs, comments, customer feedback, and survey responses. International Data Corporation (IDC) reports that the world is changing from structured data to unstructured data, which is one of the challenges facing enterprises. 80 to 90 percent of the world’s data is unstructured, and about 90 percent of it was generated in the past two years. Only about 10% of the data is stored. Even less is analyzed. Gartner predicts that by 2026, large enterprises will have tripled their unstructured data capacity in on-premises, edge, and public cloud locations compared to 2023. As the use of widespread data in enterprises increases, effective data management becomes increasingly important. Businesses can gain deep insights through data management and analytics to make profitable business decisions. Managing such large amounts of data is difficult for many organizations, especially if there is a backlog of old data or current systems are inefficient and inaccurate, while unprecedented amounts of new data are being processed every day. To make full use of big data, many technical issues need to be solved. Legacy systems and incompatible standards and formats often hinder data integration and the application of more complex analytics that create value. The IT industry is accelerating the development of data-centric artificial intelligence algorithm models. Innovation opportunities to simultaneously extend, refine, and optimize technologies originally designed for structured data so that they are more suitable for unstructured data. As a result, the demand for Hadoop from downstream customers has grown dramatically due to the increase in unstructured data from computers, smartphones, traffic cameras, RFID readers, and other devices.

Region Overview:

In 2022, the share of the Hadoop market in United States stood at 50.76%.

Company Overview:

The major players operating in the Hadoop market include Cloudera Inc., VMware, HPE, Amazon, Microsoft, etc. Among which, Cloudera Inc. ranked top in terms of sales and revenue in 2023.

Cloudera was founded in 2008 by some of the brightest minds at Silicon Valley’s leading companies, including Google, Yahoo!, Oracle, and Facebook. And in 2011, 24 engineers from the original Hadoop team at Yahoo! spun out to form Hortonworks. Both companies, who joined forces in January 2019, were founded on the belief that open source, open standards, and open markets are best. This belief remains central to our values, evidenced by our significant investments in engineers and committers working with the open source community. Today, Cloudera has offices around the globe and is headquartered in Silicon Valley, California.

Cloudera’s mission is to make data and analytics easy and accessible for everyone: by improving access to skills, software and mentorship we are increasing diversity in the technology sector and driving global economic sustainability.

Segmentation Overview:

By type, Software segment accounted for the largest share of market in 2022.

Application Overview:

By application, the IT & ITES segment occupied the biggest share from 2018 to 2022.

Key Companies in the global Hadoop market covered in Chapter 3:

Cisco Systems, Inc.
VMware
Microsoft
Dell EMC
Amazon
Cloudera Inc.
FICO
HPE
Hitachi Vantara
IBM Corp

In Chapter 4 and Chapter 14.2, on the basis of types, the Hadoop market from 2019 to 2030 is primarily split into:

Software
Services

In Chapter 5 and Chapter 14.3, on the basis of Downstream Industry, the Hadoop market from 2019 to 2030 covers:

BFSI
Government Sector
IT & ITES
Healthcare
Telecommunication
Retails
Others

Geographically, the detailed analysis of consumption, revenue, market share and growth rate, historic and forecast (2019-2030) of the following regions are covered in Chapter 8 to Chapter 14:

North America (United States, Canada)
Europe (Germany, UK, France, Italy, Spain, Russia, Netherlands, Turkey, Switzerland, Sweden)
Asia Pacific (China, Japan, South Korea, Australia, India, Indonesia, Philippines, Malaysia)
Latin America (Brazil, Mexico, Argentina)
Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa)