The global hadoop market size was valued at USD 50.01 billion in 2021. It is expected to reach USD 884.35 billion by 2030, growing at a CAGR of 37.60% during the forecast period (2022–2030).
Hadoop is a Java-based Apache open-source framework. It enables the use of straightforward programming models to distribute the processing of massive datasets, or "big data," across computer clusters. The Hadoop framework runs in a setting that offers distributed computation and storage across computer clusters. Hadoop is made to expand from a single server to thousands of machines, each offering regional analysis and storage. Applications are run using the MapReduce technique, which utilizes parallel data processing with other processes.
Additionally, it is frequently used to create programs that carry out comprehensive statistical analysis in big data. Extensive data analysis uses the distributed processing technology known as Hadoop. Due to its affordability and efficiency over more conventional data analysis tools like RDBMS, the global Hadoop market has experienced rapid growth in recent years.
A significant factor fueling the expansion of the Hadoop market is the intensifying competition in the business environment. Effective data management has become increasingly crucial as extensive data usage in businesses has increased. Enterprises can obtain deep-dive insights through data management and analysis, which enables them to make profitable business decisions. Additionally, it helps companies understand market elements like customer buying trends and market factors, allowing them to create competitive strategies and plan for the future. Most small and medium-sized businesses anticipate that setting up and running Hadoop on-premises will be challenging, particularly given the significant financial outlay needed for infrastructure and the hiring of technical staff to get Hadoop up and running successfully.
Hadoop was nearly impossible because it required a significant financial investment to install the necessary infrastructure and hire qualified personnel. However, because Hadoop providers have numerous options for their customers and users can select from a range of packages offered by suppliers, small and medium-sized businesses now have access to a robust data analytics platform. Additionally, companies might provide small businesses with templated services and clusters. Compared to the problems encountered on-premises, HaaS has several inherent advantages. Customers are only charged for the resources they use and only when consumed.
Cloud computing has expanded quickly over the past few years due to its ability to offer customers flexible, dependable, on-demand services at low prices. Due to the growth in cloud applications, data security has become a top concern. The cloud storage system is built using the open-source software Hadoop distributed file system (HDFS), which enables the storage of large amounts of data with high throughput and fault tolerance. The lack of a security model when the Hadoop system was first developed made security a significant area for improvement. The computing architecture of Hadoop presents several difficulties for data center specialists. The Hadoop user runs each task, and the file system does not follow access control units. Without reading control, it transports data in the Hadoop Distributed File System (HDFS). Data security will be crucial because Hadoop is concerned with storing sensitive data.
Many businesses are working together to make Hadoop services available to their customers. The leading companies partnering to provide a full HaaS service to their clients are cloud storage providers and developers of analytics software. For instance, the two most prominent companies in the Hadoop ample data space, Hortonworks and Cloudera, announced their merger in January 2019. With this merger, the business can offer customers a full range of solutions for getting the best data analytics out of any data. Growth into new markets or using partnerships to bring new products and technologies were identified as the primary motivations for the various business alliances made by corporations. A significant part of the development of the hadoop market share has also been capital funding.
Retailers can analyze data from both online and offline modes. E-commerce transactions and social media posts are included in these data. Big data software frameworks like Hadoop are making things easier for retailers by streamlining the process of deriving actionable insights from massive amounts of information. Hadoop is increasingly being used in the e-commerce sector for various purposes, such as personalization, dynamic pricing, enhanced customer service, managing fraud, predictive analytics, and opening lucrative market opportunities. Furthermore, by 2020, there will likely be 2.05 billion digital buyers worldwide. A global population of 7.7 billion translates to about 25% of people shopping online. In 2021, this number was projected to increase to 2.14 billion. It's expected to boost e-commerce, which will boost the market during the forecast period.
The global hadoop market is segmented by component, deployment model, organization size, and end-user.
Based on the component, the global market is bifurcated into hardware, software, and services.
The services sector contributed the most to the market and is expected to grow at a CAGR of 37% during the forecast period. An extensive data analytics framework called Hadoop services provides Hadoop consulting, integration and deployment, Hadoop training and outsourcing, and Hadoop middleware and support services. Small clusters of nodes and data involving thousands of nodes can be used with Hadoop as a Service (HaaS) for Big Data. By providing a platform that enables the cost-effective storage and processing of large-scale and complex data, Hadoop consultants offer unified data architecture for end-to-end solutions. As a result, it is anticipated that the services segment will increase during the forecast period.
A software framework enables massively distributed data analysis on low-cost servers. Hortonworks has a wealth of experience managing production-level Hadoop clusters and is a significant contributor to open-source projects like Apache Hadoop, HDFS, Pig, Hive, HBase, and ZooKeeper. The need for distributed processing to handle the burgeoning data silos is a significant driver of adopting the Hadoop Distributed File System (HDFS). Major corporations have also tended to favor HDFS because of its capacity to scale from a few servers to thousands of machines, each providing local computation and storage. As a result, businesses no longer require additional data transformation software, which spurs market expansion.
Based on the deployment model, the global market is bifurcated into on-premise, cloud, and hybrid.
The on-premise segment is the highest contributor to the market and is expected to grow at a CAGR of 34.6% during the forecast period. Instead of being installed and run at a distant location like a server farm or cloud, on-premises Hadoop runs on computers on an organization's premises. In an on-premise deployment, CDs or USB drives are used to install software on the user's computer. The adoption of on-premise Hadoop deployments is fueled by the use of Hadoop-optimized systems, which make on-premise deployments virtually instant and quick to boot.
An extensive data analytics framework called Hadoop in the cloud, a service (HaaS), uses Hadoop to store and analyze data in the cloud. Users need not purchase or set up additional infrastructure for this deployment. When utilizing Hadoop technology, a third-party vendor offers and handles cloud deployments. There are many advantages to moving from on-premise infrastructure to cloud-based infrastructure, including built-in Hadoop support, streamlined version management, flexible job configuration, managed hardware and configuration, and others that encourage end users to adopt Hadoop-as-a-Service. Data can be accessed anytime, anywhere, on tablets or smartphones with an Internet connection by using the cloud-based Hadoop platform. Greater and quicker access to data boosts productivity and fuels the market's expansion.
Based on organization size, the global market is bifurcated into large enterprises and small and medium enterprises.
The large enterprise is the highest contributor to the market and is expected to grow at a CAGR of 36.6% during the forecast period. Large businesses are defined as those with annual revenues of at least USD 500 million and staff sizes of at least 500. As Hadoop is a necessary data platform for large enterprises and the foundation of any flexible future data management platform, large businesses are increasingly incorporating it into their enterprise data management architecture. The adoption of HaaS is anticipated to be accelerated by large businesses' adoption of cloud-based platforms and their migration of processing workloads to virtual environments.
Businesses are classified as small and medium-sized if their annual revenue is less than USD 500 million and their employee size ranges from 10 to 500. Small and medium-sized businesses are now becoming more aware of the importance of consumer assistance regarding products on the market today and purchasing behavior. Hadoop solutions allow companies to analyze unprocessed data from various sources, gain insightful insights, and make market decisions. Due to the increase in SMEs in developing economies, it is anticipated that the adoption of Hadoop by SMEs will increase during the forecast period.
Based on end-user, the global market is bifurcated into manufacturing, BFSI, retail and consumer goods, IT and telecommunication, healthcare, government and defense, media and entertainment, energy and utility, and trade and transportation segment.
The IT and telecommunications segment owns the highest market share and is expected to grow at a CAGR of 29.8% during the forecast period. It is anticipated that businesses planning to use Hadoop for business purposes will opt for cloud-based Hadoop solutions rather than dealing with the difficulties associated with on-premise Hadoop. Big Data systems facilitate extensive data processing and analysis. They can handle client issues as they emerge, which is beneficial for market growth. Additionally, Hadoop adoption in CDR analysis is rising, which fuels the market's expansion.
The BFSI sector stores and analyze enormous amounts of data because of the digital revolution's numerous data access distortions. Financial companies rely on Hadoop to build data hubs that combine vast amounts of detailed and varied data, giving business applications a competitive edge. Hadoop allows companies in the financial sector to access vast amounts of richer data, including trading systems, trade execution system logs, and external sources like news feed and social media. Additionally, it supports the industry's ongoing refining and module of consumer groups while upholding a high-quality risk profile, which fuels the market's expansion.
The global hadoop market is divided into four regions, namely North America, Europe, Asia-Pacific, and LAMEA.
North America is the most significant shareholder in the global Hadoop market and is expected to grow at a CAGR of 34.3% during the forecast period. The U.S. and Canada both conduct studies on the North American market. The developed economy, widespread usage of Hadoop, and the high penetration of cloud computing in the region are the key factors that have allowed this region to capture such a significant share of the global market. Every step of the retail process now uses big data analytics to predict market demands, comprehend consumer behavior, and adjust pricing. Through predictive analytics and targeted promotions, big data in retail aids in raising conversion rates. The development of the Hadoop market is influenced by elements like the expansion of e-commerce and the rise in government funding for significant data initiatives in the United States.
Europe is expected to grow at a CAGR of 37.2%, generating USD 245.29 billion during the forecast period. The hadoop market in the UK, Germany, France, Russia, and the rest of Europe is examined. Regarding revenue, Europe holds the second-largest market share in the overall market. In the coming years, there will be many opportunities for adopting Hadoop as big data technology is increasingly used throughout Europe. The massive growth in the market for consumer and machine data is the primary driver of the European Hadoop market. Due to rapid technological advancements and improved connectivity, factors like the widespread use of smartphones and the high adoption of cloud computing have generated enormous amounts of data.
Asia-Pacific hadoop market is examined across China, India, Japan, South Korea, Australia, and the rest of Asia-Pacific. The market is growing due to the widespread use of Hadoop-based applications for real-time analytics and web-based business processes in Asia-Pacific. Furthermore, the market will have lucrative growth opportunities in the Asia-Pacific region due to the region's increased internet penetration and advancements in technology and digital infrastructure.
The demand for Hadoop in LAMEA has grown due to businesses' and consumers' rapid uptake of open-source software. One of the main drivers of the market's expansion in LAMEA is the maturing mindset of data-driven organizations to boost productivity, customer loyalty, and the rapid uptake of the Internet of Things (IoT).
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