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Global Hadoop Market Size, Share & Industry Trends Analysis Report By Enterprise Size, By Component, By Deployment Model, By Industry, By Regional Outlook and Forecast, 2021-2027

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    Report

  • 287 Pages
  • March 2022
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5590167
The Global Hadoop Market size is expected to reach $341.4 billion by 2027, rising at a market growth of 38.2% CAGR during the forecast period.



Hadoop is an open system used for processing and storing a large number of datasets, which can differ in different size between gigabytes to petabytes. Hadoop allows grouping various computers to analyze huge data sets in serial more quickly rather than using a single large machine to store and process data. Furthermore, the Hadoop ecosystem contains several devices and techniques that aid in the processing, collection, analysis, storage, and management of large amounts of data. The Hadoop market is booming due to cost-effective, rapid data processes, and vast volumes of unstructured data. Moreover, the growing importance of data analytics has a beneficial impact on market growth.

Due to its cost-effectiveness and ability to analyze data much faster, the Hadoop industry is expected to grow substantially. This software framework allows companies to manage large amounts of unorganized data at an affordable price. BFSI, retail, healthcare, government, media & entertainment, life science, and telecommunications are among the application fields where architecture can boost the market growth. Furthermore, Hadoop design has several advantages over traditional solutions such as RDBMS, which help in managing both structured and unstructured data well. Some of the key drivers driving market expansion include the necessity to monitor consumer behavior, focused marketing offers based on maintaining inventory, consumer preferences, and space, and attracting and retaining customers.

Hadoop-related tools include Hive, HBase, Flume, and others that can operate alongside Hadoop to achieved Apache project status. Hadoop is interoperable with operating systems such as Linux/GNU. If the enterprise doesn't even have a Linux/GNU operating system, it can utilize virtual box software to install Linux. There are multiple varieties of analytical tools available in the market that analyze data sets, yet Hadoop's open-source nature and ability to provide all analyses on a single platform make it more appealing.

COVID-19 Impact Analysis

The outbreak of the COVID-19 pandemic has impacted various business domains, including Hadoop market. The market has witnessed a downfall due to the restrictions imposed on the businesses. A large number of nations restricted travel around the world, to avoid the disease from spreading. However, during the recovery phase, the Hadoop business is expected to fully recover from the pandemic affects in the coming years. Multiple companies around the world have embraced a work-from-home culture, resulting in a requirement for cloud-based Hadoop solutions to handle critical data, creating a significant market opportunity. The expansion of the market is fueled by an increase in volume information data created by different sectors and the requirement to manage this data.

Market driving Factors:


Availability of low-cost data processing solutions

The surge of unorganized data from devices such as smartphones, RFID readers, PCs, traffic cameras, and others are fueling the demand for Hadoop. Unstructured data is generally changeable and diverse. The content could be in the form of a document, picture, text, video, or any other format. It also can process complex data that accounts for more than 80% of global data. Since Hadoop can manage unstructured and structured data from a data center or relational database, enabling the end-user to take more accurate judgments based on vast amounts of information, its demand in the market is also growing.

Growing popularity of smart payment technologies

Smart and contactless payments are intimately connected. Contactless payments make it much easier to transfer money between various parties. The Internet of Things automates and combines numerous processes and activities. Contactless payments are attached through gadgets such as key fobs and smart watches to connect contactless cards. ML is being used by a large number of digital enterprises to gather data from the field of commerce. From cash and paper-based payments to electronic ways of payment, public transit systems have evolved as well. Digital banking is among the growing sectors that generate real consumer value in the middle of COVID-19's record-breaking economic downturn.

Marketing Restraining Factor:


Troubles about the law and data privacy

Organizations and customers could face substantial legal consequences if data is exploited, whether intentional or unintentional. To ensure that no data usage breaches government rules, businesses should clarify terms connected to data usage, handling, and retention in project contracts. When enterprises collect profile data, the threat of identity theft grows, especially if the data is not kept secure. Viruses, Hackers, and disk damage, for example, can compromise this information. If enterprises build strategies around false data, it might cause major problems for all consumers. As a result, before using data collected from various applications, firms should carefully analyze all legal and privacy risks. Consumer privacy is the first legal danger posed by the Hadoop market. The privacy and security of personal data were the focus of laws and regulations.

Enterprise Size Outlook

Based on Enterprise Size, the market is segmented into Large Enterprises, and Small & Medium Enterprises (SMEs). The Large enterprise segment acquired the highest revenue share in the Hadoop market in 2020. Hadoop is well-known for its ability to broaden linearly. Hadoop can become a wider and stronger info constructing region for both storages of goods and data combination. Hadoop has favorable utilization cases, even if it is difficult to manage data, which is expected to accelerate the growth of the Hadoop market.

Component Outlook

Based on Component, the market is segmented into Services, Software, and Hardware. The software segment registered a substantial revenue share in the Hadoop market in 2020. Due to the extensive use of consulting and outsourcing services, along with growing use of the Hadoop framework for big data analytics in making decisions and enterprise analytics, the demand for Hadoop software is expected to further boost in the coming years.

Deployment Model Outlook

Based on Deployment Model, the market is segmented into On-premise, Cloud, and Hybrid. The On-premise segment procured the largest revenue share in the Hadoop market in 2020. Most Cloud services providers use some form of network storage, bare-metal installations typically outclass along with comprehensive command of the Hadoop software and hardware. Delay to systems that can combine as well as scaled back with physical data isolation and privacy. These features accelerate the growth of the On-premise segment.

Industry Outlook

Based on Industry, the market is segmented into IT & Telecommunications, BFSI, Retail & Consumer Goods, Manufacturing, Healthcare, Government & Defense, Media & Entertainment, Energy & Utility, Trade & Transportation, and Others. The BFSI segment recorded a substantial revenue share in the Hadoop market in 2020. Hadoop enables financial companies to access and analyze the data and provide precise information to assist in making the best decision. Other departments that use Hadoop include customer profiles and experience evaluation, targeted services, credit risk assessment, and so on.

Regional Outlook

Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa. North America dominated the Hadoop market with the highest revenue share in 2020. Due to strong growth and continued advancement in the services sector, compel business enterprises to invest in various analysis tools to maintain growth and enhance productivity. In addition, the high adoption rate of advanced and innovative technologies across this region is expected to further spur the growth of the regional market.

The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships & Collaborations.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services, Inc., Cisco Systems, Inc., Cloudera, Inc., Datameer, Inc., Hitachi Vantara LLC (Hitachi Ltd.), Fair Isaac Corporation, MapR Technologies, MarkLogic, Microsoft Corporation, and Teradata Corporation.
  • Dec 2020: Datameer came into a partnership with Google Cloud. This partnership aimed to assist mature enterprises to safely migrate their data workloads to Google Cloud while managing business continuity by allowing them to operate analytics and machine learning workflows in the hybrid & multi-cloud environments.
  • Jan 2020: Hitachi Vantara, a wholly-owned subsidiary of Hitachi took over Waterline Data, an automated data discovery platform. Through this acquisition, Waterline Data technologies is expected to support Hitachi Vantara's DataOps proficiency and is expected to become the key factor in the Lumada Data Services offering, providing consumers tighter quality control, greater visibility, better management, and improved compliance of the data.
  • Oct 2019: Teradata came into a partnership with Google Cloud, a Google suite of cloud computing services. This partnership aimed to provide the flagship solution Teradata Vantage on Google clouds, which is expected to expand Teradata's cloud footprints to all three dominant public cloud services, providing consumers greater flexibility and incomparable choice with the usage of Teradata Vantage.
  • Jun 2019: Cloudera came into a partnership with IBM, an American multinational technology corporation. Under this partnership, the companies aimed to create a joint go-to-market scheme produced to bring advanced data and AI solutions to more enterprises around the extensive Apache Hadoop environment. Additionally, IBM is expected to resell the Cloudera DataFlow and Cloudera Data Science Workbench from Cloudera Enterprise Data Hub whereas Cloudera is expected to resell IBM's BigSQL and Watson Studio.
  • Jun 2019: Hitachi Vantara introduced Pentaho 8.3 platform. The platform offers to add on features that enhance integration and data visibility with various cloud services such as Amazon Kinesis for actual-time data streaming.
  • Apr 2019: Microsoft introduced up-gradation in its open-source analytics services working on Azure. This expansion aimed to assimilate improvements of Apache Hive and other open-source analytics frameworks with the new version of Hadoop.
  • Jan 2019: Cloudera merged with Hortonworks, a data software company based in Santa Clara. This merger aimed to deliver the first organization data cloud releasing the power of any data, functioning in the cloud from the Edge to AI, on a 100% open-source data platform. Additionally, organization data cloud supports multi as well as hybrid cloud distribution, providing freedom to perform machine learning and analytics with data without lock-in.

Scope of the Study


Market Segments Covered in the Report:


By Enterprise Size

  • Large Enterprises
  • Small & Medium Enterprises (SMEs)

By Component

  • Services
  • Software
  • Hardware

By Deployment Model

  • On-premise
  • Cloud
  • Hybrid

By Industry

  • IT & Telecommunications
  • BFSI
  • Retail & Consumer Goods
  • Manufacturing
  • Healthcare
  • Government & Defense
  • Media & Entertainment
  • Energy & Utility
  • Trade & Transportation
  • Others

By Geography

  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players


List of Companies Profiled in the Report:

  • Amazon Web Services, Inc.
  • Cisco Systems, Inc.
  • Cloudera, Inc.
  • Datameer, Inc.
  • Hitachi Vantara LLC (Hitachi Ltd.)
  • Fair Isaac Corporation
  • MapR Technologies
  • MarkLogic
  • Microsoft Corporation
  • Teradata Corporation

Unique Offerings from the publisher

  • Exhaustive coverage
  • The highest number of market tables and figures
  • Subscription-based model available
  • Guaranteed best price
  • Assured post sales research support with 10% customization free
Frequently Asked Questions about the Global Hadoop Market

What is the estimated value of the Global Hadoop Market?

The Global Hadoop Market was estimated to be valued at $35259 Billion in 2020.

What is the growth rate of the Global Hadoop Market?

The growth rate of the Global Hadoop Market is 38.3%, with an estimated value of $341372 Billion by 2027.

What is the forecasted size of the Global Hadoop Market?

The Global Hadoop Market is estimated to be worth $341372 Billion by 2027.

Who are the key companies in the Global Hadoop Market?

Key companies in the Global Hadoop Market include Amazon Web Services, Inc., Cisco Systems, Inc., Cloudera, Inc., Datameer, Inc., Hitachi Vantara LLC (Hitachi Ltd.), Fair Isaac Corporation, MapR Technologies, MarkLogic and Teradata Corporation.

Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Hadoop Market, by Enterprise Size
1.4.2 Global Hadoop Market, by Component
1.4.3 Global Hadoop Market, by Deployment Model
1.4.4 Global Hadoop Market, by Industry
1.4.5 Global Hadoop Market, by Geography
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Market Share Analysis, 2020
3.1.1 Company and Respective Products
3.1.2 Strategies deployed in Hadoop Market
Chapter 4. Global Hadoop Market by Enterprise Size
4.1 Global Large Enterprises Market by Region
4.2 Global Small & Medium Enterprises (SMEs) Market by Region
Chapter 5. Global Hadoop Market by Component
5.1 Global Services Market by Region
5.2 Global Software Market by Region
5.3 Global Hardware Market by Region
Chapter 6. Global Hadoop Market by Deployment Model
6.1 Global On-premise Market by Region
6.2 Global Cloud Market by Region
6.3 Global Hybrid Market by Region
Chapter 7. Global Hadoop Market by Industry
7.1 Global IT & Telecommunications Market by Region
7.2 Global BFSI Market by Region
7.3 Global Retail & Consumer Goods Market by Region
7.4 Global Manufacturing Market by Region
7.5 Global Healthcare Market by Region
7.6 Global Government & Defense Market by Region
7.7 Global Media & Entertainment Market by Region
7.8 Global Energy & Utility Market by Region
7.9 Global Trade & Transportation Market by Region
7.1 Global Others Market by Region
Chapter 8. Global Hadoop Market by Region
8.1 North America Hadoop Market
8.1.1 North America Hadoop Market by Enterprise Size
8.1.1.1 North America Large Enterprises Market by Country
8.1.1.2 North America Small & Medium Enterprises (SMEs) Market by Country
8.1.2 North America Hadoop Market by Component
8.1.2.1 North America Services Market by Country
8.1.2.2 North America Software Market by Country
8.1.2.3 North America Hardware Market by Country
8.1.3 North America Hadoop Market by Deployment Model
8.1.3.1 North America On-premise Market by Country
8.1.3.2 North America Cloud Market by Country
8.1.3.3 North America Hybrid Market by Country
8.1.4 North America Hadoop Market by Industry
8.1.4.1 North America IT & Telecommunications Market by Country
8.1.4.2 North America BFSI Market by Country
8.1.4.3 North America Retail & Consumer Goods Market by Country
8.1.4.4 North America Manufacturing Market by Country
8.1.4.5 North America Healthcare Market by Country
8.1.4.6 North America Government & Defense Market by Country
8.1.4.7 North America Media & Entertainment Market by Country
8.1.4.8 North America Energy & Utility Market by Country
8.1.4.9 North America Trade & Transportation Market by Country
8.1.4.10 North America Others Market by Country
8.1.5 North America Hadoop Market by Country
8.1.5.1 US Hadoop Market
8.1.5.1.1 US Hadoop Market by Enterprise Size
8.1.5.1.2 US Hadoop Market by Component
8.1.5.1.3 US Hadoop Market by Deployment Model
8.1.5.1.4 US Hadoop Market by Industry
8.1.5.2 Canada Hadoop Market
8.1.5.2.1 Canada Hadoop Market by Enterprise Size
8.1.5.2.2 Canada Hadoop Market by Component
8.1.5.2.3 Canada Hadoop Market by Deployment Model
8.1.5.2.4 Canada Hadoop Market by Industry
8.1.5.3 Mexico Hadoop Market
8.1.5.3.1 Mexico Hadoop Market by Enterprise Size
8.1.5.3.2 Mexico Hadoop Market by Component
8.1.5.3.3 Mexico Hadoop Market by Deployment Model
8.1.5.3.4 Mexico Hadoop Market by Industry
8.1.5.4 Rest of North America Hadoop Market
8.1.5.4.1 Rest of North America Hadoop Market by Enterprise Size
8.1.5.4.2 Rest of North America Hadoop Market by Component
8.1.5.4.3 Rest of North America Hadoop Market by Deployment Model
8.1.5.4.4 Rest of North America Hadoop Market by Industry
8.2 Europe Hadoop Market
8.2.1 Europe Hadoop Market by Enterprise Size
8.2.1.1 Europe Large Enterprises Market by Country
8.2.1.2 Europe Small & Medium Enterprises (SMEs) Market by Country
8.2.2 Europe Hadoop Market by Component
8.2.2.1 Europe Services Market by Country
8.2.2.2 Europe Software Market by Country
8.2.2.3 Europe Hardware Market by Country
8.2.3 Europe Hadoop Market by Deployment Model
8.2.3.1 Europe On-premise Market by Country
8.2.3.2 Europe Cloud Market by Country
8.2.3.3 Europe Hybrid Market by Country
8.2.4 Europe Hadoop Market by Industry
8.2.4.1 Europe IT & Telecommunications Market by Country
8.2.4.2 Europe BFSI Market by Country
8.2.4.3 Europe Retail & Consumer Goods Market by Country
8.2.4.4 Europe Manufacturing Market by Country
8.2.4.5 Europe Healthcare Market by Country
8.2.4.6 Europe Government & Defense Market by Country
8.2.4.7 Europe Media & Entertainment Market by Country
8.2.4.8 Europe Energy & Utility Market by Country
8.2.4.9 Europe Trade & Transportation Market by Country
8.2.4.10 Europe Others Market by Country
8.2.5 Europe Hadoop Market by Country
8.2.5.1 Germany Hadoop Market
8.2.5.1.1 Germany Hadoop Market by Enterprise Size
8.2.5.1.2 Germany Hadoop Market by Component
8.2.5.1.3 Germany Hadoop Market by Deployment Model
8.2.5.1.4 Germany Hadoop Market by Industry
8.2.5.2 UK Hadoop Market
8.2.5.2.1 UK Hadoop Market by Enterprise Size
8.2.5.2.2 UK Hadoop Market by Component
8.2.5.2.3 UK Hadoop Market by Deployment Model
8.2.5.2.4 UK Hadoop Market by Industry
8.2.5.3 France Hadoop Market
8.2.5.3.1 France Hadoop Market by Enterprise Size
8.2.5.3.2 France Hadoop Market by Component
8.2.5.3.3 France Hadoop Market by Deployment Model
8.2.5.3.4 France Hadoop Market by Industry
8.2.5.4 Russia Hadoop Market
8.2.5.4.1 Russia Hadoop Market by Enterprise Size
8.2.5.4.2 Russia Hadoop Market by Component
8.2.5.4.3 Russia Hadoop Market by Deployment Model
8.2.5.4.4 Russia Hadoop Market by Industry
8.2.5.5 Spain Hadoop Market
8.2.5.5.1 Spain Hadoop Market by Enterprise Size
8.2.5.5.2 Spain Hadoop Market by Component
8.2.5.5.3 Spain Hadoop Market by Deployment Model
8.2.5.5.4 Spain Hadoop Market by Industry
8.2.5.6 Italy Hadoop Market
8.2.5.6.1 Italy Hadoop Market by Enterprise Size
8.2.5.6.2 Italy Hadoop Market by Component
8.2.5.6.3 Italy Hadoop Market by Deployment Model
8.2.5.6.4 Italy Hadoop Market by Industry
8.2.5.7 Rest of Europe Hadoop Market
8.2.5.7.1 Rest of Europe Hadoop Market by Enterprise Size
8.2.5.7.2 Rest of Europe Hadoop Market by Component
8.2.5.7.3 Rest of Europe Hadoop Market by Deployment Model
8.2.5.7.4 Rest of Europe Hadoop Market by Industry
8.3 Asia Pacific Hadoop Market
8.3.1 Asia Pacific Hadoop Market by Enterprise Size
8.3.1.1 Asia Pacific Large Enterprises Market by Country
8.3.1.2 Asia Pacific Small & Medium Enterprises (SMEs) Market by Country
8.3.2 Asia Pacific Hadoop Market by Component
8.3.2.1 Asia Pacific Services Market by Country
8.3.2.2 Asia Pacific Software Market by Country
8.3.2.3 Asia Pacific Hardware Market by Country
8.3.3 Asia Pacific Hadoop Market by Deployment Model
8.3.3.1 Asia Pacific On-premise Market by Country
8.3.3.2 Asia Pacific Cloud Market by Country
8.3.3.3 Asia Pacific Hybrid Market by Country
8.3.4 Asia Pacific Hadoop Market by Industry
8.3.4.1 Asia Pacific IT & Telecommunications Market by Country
8.3.4.2 Asia Pacific BFSI Market by Country
8.3.4.3 Asia Pacific Retail & Consumer Goods Market by Country
8.3.4.4 Asia Pacific Manufacturing Market by Country
8.3.4.5 Asia Pacific Healthcare Market by Country
8.3.4.6 Asia Pacific Government & Defense Market by Country
8.3.4.7 Asia Pacific Media & Entertainment Market by Country
8.3.4.8 Asia Pacific Energy & Utility Market by Country
8.3.4.9 Asia Pacific Trade & Transportation Market by Country
8.3.4.10 Asia Pacific Others Market by Country
8.3.5 Asia Pacific Hadoop Market by Country
8.3.5.1 China Hadoop Market
8.3.5.1.1 China Hadoop Market by Enterprise Size
8.3.5.1.2 China Hadoop Market by Component
8.3.5.1.3 China Hadoop Market by Deployment Model
8.3.5.1.4 China Hadoop Market by Industry
8.3.5.2 Japan Hadoop Market
8.3.5.2.1 Japan Hadoop Market by Enterprise Size
8.3.5.2.2 Japan Hadoop Market by Component
8.3.5.2.3 Japan Hadoop Market by Deployment Model
8.3.5.2.4 Japan Hadoop Market by Industry
8.3.5.3 India Hadoop Market
8.3.5.3.1 India Hadoop Market by Enterprise Size
8.3.5.3.2 India Hadoop Market by Component
8.3.5.3.3 India Hadoop Market by Deployment Model
8.3.5.3.4 India Hadoop Market by Industry
8.3.5.4 South Korea Hadoop Market
8.3.5.4.1 South Korea Hadoop Market by Enterprise Size
8.3.5.4.2 South Korea Hadoop Market by Component
8.3.5.4.3 South Korea Hadoop Market by Deployment Model
8.3.5.4.4 South Korea Hadoop Market by Industry
8.3.5.5 Singapore Hadoop Market
8.3.5.5.1 Singapore Hadoop Market by Enterprise Size
8.3.5.5.2 Singapore Hadoop Market by Component
8.3.5.5.3 Singapore Hadoop Market by Deployment Model
8.3.5.5.4 Singapore Hadoop Market by Industry
8.3.5.6 Malaysia Hadoop Market
8.3.5.6.1 Malaysia Hadoop Market by Enterprise Size
8.3.5.6.2 Malaysia Hadoop Market by Component
8.3.5.6.3 Malaysia Hadoop Market by Deployment Model
8.3.5.6.4 Malaysia Hadoop Market by Industry
8.3.5.7 Rest of Asia Pacific Hadoop Market
8.3.5.7.1 Rest of Asia Pacific Hadoop Market by Enterprise Size
8.3.5.7.2 Rest of Asia Pacific Hadoop Market by Component
8.3.5.7.3 Rest of Asia Pacific Hadoop Market by Deployment Model
8.3.5.7.4 Rest of Asia Pacific Hadoop Market by Industry
8.4 LAMEA Hadoop Market
8.4.1 LAMEA Hadoop Market by Enterprise Size
8.4.1.1 LAMEA Large Enterprises Market by Country
8.4.1.2 LAMEA Small & Medium Enterprises (SMEs) Market by Country
8.4.2 LAMEA Hadoop Market by Component
8.4.2.1 LAMEA Services Market by Country
8.4.2.2 LAMEA Software Market by Country
8.4.2.3 LAMEA Hardware Market by Country
8.4.3 LAMEA Hadoop Market by Deployment Model
8.4.3.1 LAMEA On-premise Market by Country
8.4.3.2 LAMEA Cloud Market by Country
8.4.3.3 LAMEA Hybrid Market by Country
8.4.4 LAMEA Hadoop Market by Industry
8.4.4.1 LAMEA IT & Telecommunications Market by Country
8.4.4.2 LAMEA BFSI Market by Country
8.4.4.3 LAMEA Retail & Consumer Goods Market by Country
8.4.4.4 LAMEA Manufacturing Market by Country
8.4.4.5 LAMEA Healthcare Market by Country
8.4.4.6 LAMEA Government & Defense Market by Country
8.4.4.7 LAMEA Media & Entertainment Market by Country
8.4.4.8 LAMEA Energy & Utility Market by Country
8.4.4.9 LAMEA Trade & Transportation Market by Country
8.4.4.10 LAMEA Others Market by Country
8.4.5 LAMEA Hadoop Market by Country
8.4.5.1 Brazil Hadoop Market
8.4.5.1.1 Brazil Hadoop Market by Enterprise Size
8.4.5.1.2 Brazil Hadoop Market by Component
8.4.5.1.3 Brazil Hadoop Market by Deployment Model
8.4.5.1.4 Brazil Hadoop Market by Industry
8.4.5.2 Argentina Hadoop Market
8.4.5.2.1 Argentina Hadoop Market by Enterprise Size
8.4.5.2.2 Argentina Hadoop Market by Component
8.4.5.2.3 Argentina Hadoop Market by Deployment Model
8.4.5.2.4 Argentina Hadoop Market by Industry
8.4.5.3 UAE Hadoop Market
8.4.5.3.1 UAE Hadoop Market by Enterprise Size
8.4.5.3.2 UAE Hadoop Market by Component
8.4.5.3.3 UAE Hadoop Market by Deployment Model
8.4.5.3.4 UAE Hadoop Market by Industry
8.4.5.4 Saudi Arabia Hadoop Market
8.4.5.4.1 Saudi Arabia Hadoop Market by Enterprise Size
8.4.5.4.2 Saudi Arabia Hadoop Market by Component
8.4.5.4.3 Saudi Arabia Hadoop Market by Deployment Model
8.4.5.4.4 Saudi Arabia Hadoop Market by Industry
8.4.5.5 South Africa Hadoop Market
8.4.5.5.1 South Africa Hadoop Market by Enterprise Size
8.4.5.5.2 South Africa Hadoop Market by Component
8.4.5.5.3 South Africa Hadoop Market by Deployment Model
8.4.5.5.4 South Africa Hadoop Market by Industry
8.4.5.6 Nigeria Hadoop Market
8.4.5.6.1 Nigeria Hadoop Market by Enterprise Size
8.4.5.6.2 Nigeria Hadoop Market by Component
8.4.5.6.3 Nigeria Hadoop Market by Deployment Model
8.4.5.6.4 Nigeria Hadoop Market by Industry
8.4.5.7 Rest of LAMEA Hadoop Market
8.4.5.7.1 Rest of LAMEA Hadoop Market by Enterprise Size
8.4.5.7.2 Rest of LAMEA Hadoop Market by Component
8.4.5.7.3 Rest of LAMEA Hadoop Market by Deployment Model
8.4.5.7.4 Rest of LAMEA Hadoop Market by Industry
Chapter 9. Company Profiles
9.1 Cloudera, Inc.
9.1.1 Company Overview
9.1.2 Financial Analysis
9.1.3 Segmental Analysis
9.1.4 Research & Development Expense
9.1.5 Recent strategies and developments:
9.1.5.1 Partnerships, Collaborations, and Agreements:
9.1.5.2 Acquisitions and Mergers:
9.2 Microsoft Corporation
9.2.1 Company Overview
9.2.2 Financial Analysis
9.2.3 Segmental and Regional Analysis
9.2.4 Research & Development Expenses
9.2.5 Recent strategies and developments:
9.2.5.1 Product Launches and Product Expansions:
9.3 Teradata Corporation
9.3.1 Company Overview
9.3.2 Financial Analysis
9.3.3 Regional Analysis
9.3.4 Research & Development Expense
9.3.5 Recent strategies and developments:
9.3.5.1 Partnerships, Collaborations and Agreements:
9.3.6 SWOT Analysis
9.4 Datameer, Inc.
9.4.1 Company Overview
9.4.2 Recent strategies and developments:
9.4.2.1 Partnerships, Collaborations, and Agreements:
9.5 Hitachi Vantara LLC (Hitachi Ltd.)
9.5.1 Company Overview
9.5.2 Financial Analysis
9.5.3 Segmental and Regional Analysis
9.5.4 Research & Development Expenses
9.5.5 Recent strategies and developments:
9.5.5.1 Product Launches and Product Expansions:
9.5.5.2 Acquisition and Mergers:
9.6 Amazon Web Services, Inc.
9.6.1 Company Overview
9.6.2 Financial Analysis
9.6.3 Segmental and Regional Analysis
9.7 Cisco Systems, Inc.
9.7.1 Company Overview
9.7.2 Financial Analysis
9.7.3 Regional Analysis
9.7.4 Research & Development Expense
9.8 Fair Isaac Corporation (FICO)
9.8.1 Company Overview
9.8.2 Financial Analysis
9.8.3 Segmental and Regional Analysis
9.8.4 Research & Development Expenses
9.9 Hewlett Packard Enterprise Company
9.9.1 Company Overview
9.9.2 Financial Analysis
9.9.3 Segmental and Regional Analysis
9.9.4 Research & Development Expense
9.9.5 SWOT Analysis
9.10. MarkLogic Corporation
9.10.1 Company Overview

Companies Mentioned

  • Amazon Web Services, Inc.
  • Cisco Systems, Inc.
  • Cloudera, Inc.
  • Datameer, Inc.
  • Hitachi Vantara LLC (Hitachi Ltd.)
  • Fair Isaac Corporation
  • MapR Technologies
  • MarkLogic
  • Microsoft Corporation
  • Teradata Corporation

Methodology

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