Hadoop Distribution Market Outlook (2023 to 2033)

The global Hadoop distribution market is anticipated to generate revenues of US$ 92.7 billion in 2023. Demand for hadoop distribution is anticipated to expand at a CAGR of 37.4% and reach US$ 2,223.2 billion by 2033.

Technological Advancement Correlates with the Increased Profit margins in the Industry

Countless technical developments throughout the world have greatly accelerated economic growth. This advancement includes:

  • 5G
  • Blockchain
  • Cloud services
  • Internet of Things (IoT)
  • Artificial Intelligence (AI)

Together with other changes to economies throughout the world, the expansion of the ICT industry has made a substantial contribution to GDP growth. Also, the IT sector's creation of goods and services boosts economic expansion and development. This growth increases the need for big data solutions, which in turn increases the pace of hadoop distribution adoption.

E-commerce Industry: Accelerating Trend in the Global Industry

Retailers have access to both online and offline data analysis. These data include posts on social media and e-commerce transactions. The process of obtaining useful insights from vast volumes of data is being streamlined for retailers by big data software frameworks like Hadoop.

In the e-commerce industry, Hadoop is being utilized more often for a variety of tasks, including predictive analytics, customization, improved customer service, dynamic pricing, monitoring fraud, and creating profitable new market prospects.

Privacy Concern Act as a Key Milestone in the Market

Due to its capacity to provide clients with adaptable, trustworthy, on-demand services at affordable costs, cloud computing has experienced rapid growth over the past several years. Data security has been elevated to a top priority as a result of the expansion of cloud applications.

The Hadoop distributed file system (HDFS), which allows for the storage of massive volumes of data with high throughput and fault tolerance, is used to build the cloud storage system. Security was the key area for development when the Hadoop system was initially established as there wasn't a security paradigm.

For experts in data centers, Hadoop's computational design poses several challenges. Service vendors need to overcome these challenges to create a strong base in the market.

Attributes Details
Hadoop Distribution Market CAGR (2023 to 2033) 37.4%
Hadoop Distribution Market Size (2023) US$ 92.7 billion
Hadoop Distribution Market Size (2033) US$ 2,223.2 billion

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Historical Development and Hadoop Distribution Industry Analysis (2018 to 2022 vs. 2023 to 2033)

Demand Analysis from 2018 to 2022

From 2018 to 2022, the industry had a CAGR of 14.3%, which is expected to develop at a 37.4% CAGR during the forecast period. The market's value increased, going from US$ 20.94 billion in 2018 to US$ 46.69 billion in 2022 as it expanded.

To make Hadoop services available to their clients, many companies collaborated. Cloud storage firms and makers of analytics software are the top businesses that collaborate to offer a comprehensive HaaS solution to their clients.

Future Market Scope (2023 to 2033)

Hadoop is growing increasingly popular among businesses in all industries that deal with massive datasets thanks to its capacity to scale up horizontally by adding nodes to clusters as needed. This includes:

  • Healthcare providers
  • Financial institutions
  • Retailers
  • Logistics companies

Due to the growth of unstructured data from devices like smartphones, RFID readers, computers, traffic cameras, and other devices, the adoption of Hadoop distribution is growing significantly.

Between 2022 and 2023, this is likely to create opportunity growth of 4.4x and leads to an expected valuation of US$ 2,223.2 billion.

Region Analysis

Hadoop Distribution in the North America Market Increasing at Rapid Pace

Both the United States and Canada are growing their share of the North American market. The key drivers boosting the market size include the region's established economy, broad use of Hadoop distributions, and high penetration of cloud computing.

Big data analytics are being used at every stage of the retail process to forecast market demand, understand consumer behavior, and modify prices. Big data in retail helps to increase conversion rates with predictive analytics and customized marketing.

The growth of e-commerce and the increase in government financing for big data solutions in the United States are primary factors that have an impact on the Hadoop distribution industry development.

Key Players in Europe Effectively Contributing to the Hadoop Distribution Demand

FMI Market report looks into the hadoop distribution sector in the United Kingdom, Germany, Russia, France, and the rest of Europe. In terms of sales, Europe commands the second-leading market share globally.

Since big data technology is rapidly employed in Europe, there are several prospects for the adoption of Hadoop in the upcoming years. The main force behind the rapid expansion of the consumer and machine data markets in Europe is Hadoop distribution.

Factors like the widespread usage of smartphones and the high adoption of cloud computing have created vast volumes of data due to quick technical improvements and enhanced connectivity.

Profitable Projects in the Asia Pacific Lead the Market's Income Streams

The market is growing as a result of the increased use of Hadoop-based applications for real-time analytics and web-based business processes in Asia-Pacific. The region also provides the market with substantial development prospects as a result of the area's rising internet adoption and advances in technology and digital infrastructure.

Projects in China Market

  • Cloud by Tencent TKE Hadoop: TKE Hadoop is a proprietary Hadoop distribution offered by Tencent Cloud, a significant participant in the Chinese cloud computing industry. Businesses make use of the potential of Hadoop and related technologies due to its dependable and high-performance platform for big data processing and analytics.
  • Inspur K-UX: K-UX is an enterprise-grade Hadoop distribution that was created by Inspur, a well-known Chinese IT business. K-UX specializes in supplying comprehensive data management and analytics solutions together with high-performance and dependable data processing capabilities.

Projects in Indian Market

  • Qubole offers its Data Service, which offers a managed environment for big data processing and analytics.
    • Qubole is a cloud-native data platform. Many Hadoop distributions, including Hortonworks, Cloudera, and Apache Hadoop, are supported by QDS.
    • It makes Hadoop cluster setup and maintenance simpler, making it simpler for businesses to use big data technology.
  • MapmyIndia's MapR-FS: A distributed file system based on Hadoop called MapR-FS was created by MapmyIndia, a firm that provides mapping and location-based services in India.
    • For storing and analyzing massive amounts of data, MapR-FS provides great performance, scalability, and dependability.
    • It is mostly used in mapping and navigation systems and was created with geospatial applications in mind.
Sudip Saha
Sudip Saha

Principal Consultant

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Category Analysis

Which Components Dominate the Hadoop Distribution Market?

The market's leading contributor, the services sector, is anticipated to expand at a significant CAGR during the projected period. Hadoop as a Service (HaaS) for Big Data is utilized with small clusters of nodes and data comprising tens of thousands of nodes.

Hadoop consultants offer unified data architecture for end-to-end solutions by offering a platform that enables the cost-effective storage and processing of large-scale and complicated data. The services category is thus expected to grow throughout the projection period.

Due to its ability to grow from a few servers to thousands of devices, each of which provides local processing and storage, key organizations have also opted to adopt HDFS. Businesses no longer need extra data transformation software as a consequence, which stimulates market growth.

Which End User Has High Potential in the Market?

The IT and telecommunication segment is expected to dominate the market during the forecast period. It is expected that companies wanting to use Hadoop for commercial reasons are likely to choose cloud-based Hadoop solutions rather than deal with the challenges posed by on-premise Hadoop.

Massive data processing and analysis are facilitated by big data platforms. They are capable of handling new customer difficulties, which is advantageous for market expansion. The market is growing as a result of Hadoop's increasing use in CDR analysis.

Due to the multiple data access distortions caused by the digital revolution, the BFSI industry stores and analyzes vast volumes of data. Financial institutions rely on Hadoop to create data centers that pool enormous volumes of intricate and diverse data, providing business applications a competitive edge.

What Emerges the Need for Commercial Hadoop Distribution?

The shortcomings and problems with the open-source hadoop are resolved by vendor versions of the software. A significant proportion of hadoop distribution suppliers offer technical support and help to clients, making it simple for them to utilize hadoop for high-level activities and mission-critical applications.

Top Commercial Hadoop Distribution Vendors Leading the Market Share

The Hadoop distribution market share is influenced by the most well-liked distribution and successful projects. Cloudera distribution, which includes Apache Hadoop, is one of the most popular projects at the moment.

Due to its extensive collection of tools, enterprise-grade capabilities, and strong support services, CDH has been widely accepted by numerous enterprises.

  • Hortonworks Hadoop Distribution: In the IT industry, open-source Hadoop distributions are driven by Hortonworks, a firm that specializes in Hadoop exclusively. Hortonworks' key objective is to use Hadoop as the open data platform for all of its inventions and to create a partner ecosystem that hastens the adoption of Hadoop by businesses.
  • Cloudera Hadoop Distribution: Since 2008, Cloudera Hadoop Vendor has been at the top of the list of big data suppliers for its work in making Hadoop a trustworthy platform for commercial use.
    • The United States Army, AllState, and Monsanto are just a few of the almost 350 paying clients of the Cloudera Hadoop provider.
    • Some of them brag about setting up 1000 nodes on a Hadoop cluster to process one petabyte of data using big data analytics.
  • IBM Infosphere Biginsights hadoop Distribution: A widely used IBM Hadoop distribution, IBM Infosphere BigInsights integrates enterprise-grade features with Hadoop.
    • BigSheets and BigInsights are offered as a service by IBM through its Smartcloud Enterprise Infrastructure.
    • Users of IBM Hadoop distributions quickly set up and migrate data to Hadoop clusters, processing data at a rate of 60 cents per Hadoop cluster, per hour.

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Key Players in the Hadoop Distribution Market Powering Big Data Success

Circulations from Hadoop distribution vendors are reliable for prompt reactions to updates, fixes, and issue discovery. This enables additional add-on tools to allow users to personalize their programs.

The demand for Hadoop distribution is growing as more and more firms are understanding the value of data-driven decision-making. Important players are concentrating on big data dissemination, which creates new market prospects.

The large financial investment required for infrastructure and the employment of technical employees to effectively launch Hadoop. The main small and medium-sized firms foresee difficulty in setting up and operating Hadoop on-premises. They need to comprehend effective strategies and trends for market success.

Recent Development:

  • Cloudera Data Platform (CDP) One, a software as a service (SaaS) product that provides rapid and simple self-service analytics and exploratory data science on any data, was released in August 2022, according to the hybrid data business Cloudera.
  • Two of the top Hadoop producers and distributors, Cloudera and Hortonworks, announced a merger in March 2019 and are now known as Cloudera.

Key Players

  • Amazon Web Services
  • Cisco Systems, Inc.
  • Hitachi Data Systems
  • Datameer, Inc.
  • Cloudera, Inc.
  • MarkLogic
  • Teradata Corporation.
  • Fair Isaac Corporation
  • MapR Technologies
  • Microsoft Corporation

Key Segments

By Component:

  • Hardware
  • Software
  • Services

By Application:

  • Manufacturing
  • BFSI
  • Retail & Consumer Goods
  • IT & Telecommunications
  • Healthcare
  • Government & Defense
  • Energy & Utility
  • Others

By Region:

  • North America
  • Latin America
  • Europe
  • East Asia
  • South Asia
  • Oceania
  • Middle East & Africa (MEA)

Frequently Asked Questions

What is the Hadoop Distribution Market CAGR for 2033?

The Hadoop Distribution Market Compound Annual Growth Rate (CAGR) for 2033 is 37.4%.

How Big is the Hadoop Distribution Market?

The market is valued at US$ 92.7 million in 2023.

What is the projected market value of the global Hadoop Distribution Market for 2033?

The projected market value of the market for 2033 is US$ 2,232.2 million.

What Key Trends are Driving the Hadoop Distribution Market?

The rise of big data and Hadoop for storage, cloud adoption, scalability, security, compliance, and Internet of Things (IoT) data analysis.

What Limits the Growth Potential of the Hadoop Distribution Market?

Factors such as complex learning, high costs, skill shortage, competition, and hardware demands limit the market.

Table of Content

1. Executive Summary

    1.1. Global Market Outlook

    1.2. Demand-side Trends

    1.3. Supply-side Trends

    1.4. Technology Roadmap Analysis

    1.5. Analysis and Recommendations

2. Market Overview

    2.1. Market Coverage / Taxonomy

    2.2. Market Definition / Scope / Limitations

3. Market Background

    3.1. Market Dynamics

        3.1.1. Drivers

        3.1.2. Restraints

        3.1.3. Opportunity

        3.1.4. Trends

    3.2. Scenario Forecast

        3.2.1. Demand in Optimistic Scenario

        3.2.2. Demand in Likely Scenario

        3.2.3. Demand in Conservative Scenario

    3.3. Opportunity Map Analysis

    3.4. Investment Feasibility Matrix

    3.5. PESTLE and Porter’s Analysis

    3.6. Regulatory Landscape

        3.6.1. By Key Regions

        3.6.2. By Key Countries

    3.7. Regional Parent Market Outlook

4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033

    4.1. Historical Market Size Value (US$ Million) Analysis, 2018 to 2022

    4.2. Current and Future Market Size Value (US$ Million) Projections, 2023 to 2033

        4.2.1. Y-o-Y Growth Trend Analysis

        4.2.2. Absolute $ Opportunity Analysis

5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Component

    5.1. Introduction / Key Findings

    5.2. Historical Market Size Value (US$ Million) Analysis By Component, 2018 to 2022

    5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Component, 2023 to 2033

        5.3.1. Hardware

        5.3.2. Software & Services

    5.4. Y-o-Y Growth Trend Analysis By Component, 2018 to 2022

    5.5. Absolute $ Opportunity Analysis By Component, 2023 to 2033

6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Application

    6.1. Introduction / Key Findings

    6.2. Historical Market Size Value (US$ Million) Analysis By Application, 2018 to 2022

    6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Application, 2023 to 2033

        6.3.1. Manufacturing

        6.3.2. BFSI

        6.3.3. Retail & Consumer Goods

        6.3.4. IT & Telecommunications

        6.3.5. Healthcare

        6.3.6. Government & Defense

        6.3.7. Energy & Utility

        6.3.8. Others

    6.4. Y-o-Y Growth Trend Analysis By Application, 2018 to 2022

    6.5. Absolute $ Opportunity Analysis By Application, 2023 to 2033

7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region

    7.1. Introduction

    7.2. Historical Market Size Value (US$ Million) Analysis By Region, 2018 to 2022

    7.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2023 to 2033

        7.3.1. North America

        7.3.2. Latin America

        7.3.3. Europe

        7.3.4. South Asia

        7.3.5. East Asia

        7.3.6. Oceania

        7.3.7. MEA

    7.4. Market Attractiveness Analysis By Region

8. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    8.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    8.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        8.2.1. By Country

            8.2.1.1. USA

            8.2.1.2. Canada

        8.2.2. By Component

        8.2.3. By Application

    8.3. Market Attractiveness Analysis

        8.3.1. By Country

        8.3.2. By Component

        8.3.3. By Application

    8.4. Key Takeaways

9. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    9.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    9.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        9.2.1. By Country

            9.2.1.1. Brazil

            9.2.1.2. Mexico

            9.2.1.3. Rest of Latin America

        9.2.2. By Component

        9.2.3. By Application

    9.3. Market Attractiveness Analysis

        9.3.1. By Country

        9.3.2. By Component

        9.3.3. By Application

    9.4. Key Takeaways

10. Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    10.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    10.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        10.2.1. By Country

            10.2.1.1. Germany

            10.2.1.2. UK

            10.2.1.3. France

            10.2.1.4. Spain

            10.2.1.5. Italy

            10.2.1.6. Rest of Europe

        10.2.2. By Component

        10.2.3. By Application

    10.3. Market Attractiveness Analysis

        10.3.1. By Country

        10.3.2. By Component

        10.3.3. By Application

    10.4. Key Takeaways

11. South Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    11.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    11.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        11.2.1. By Country

            11.2.1.1. India

            11.2.1.2. Malaysia

            11.2.1.3. Singapore

            11.2.1.4. Thailand

            11.2.1.5. Rest of South Asia

        11.2.2. By Component

        11.2.3. By Application

    11.3. Market Attractiveness Analysis

        11.3.1. By Country

        11.3.2. By Component

        11.3.3. By Application

    11.4. Key Takeaways

12. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        12.2.1. By Country

            12.2.1.1. China

            12.2.1.2. Japan

            12.2.1.3. South Korea

        12.2.2. By Component

        12.2.3. By Application

    12.3. Market Attractiveness Analysis

        12.3.1. By Country

        12.3.2. By Component

        12.3.3. By Application

    12.4. Key Takeaways

13. Oceania Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        13.2.1. By Country

            13.2.1.1. Australia

            13.2.1.2. New Zealand

        13.2.2. By Component

        13.2.3. By Application

    13.3. Market Attractiveness Analysis

        13.3.1. By Country

        13.3.2. By Component

        13.3.3. By Application

    13.4. Key Takeaways

14. MEA Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country

    14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033

        14.2.1. By Country

            14.2.1.1. GCC Countries

            14.2.1.2. South Africa

            14.2.1.3. Israel

            14.2.1.4. Rest of MEA

        14.2.2. By Component

        14.2.3. By Application

    14.3. Market Attractiveness Analysis

        14.3.1. By Country

        14.3.2. By Component

        14.3.3. By Application

    14.4. Key Takeaways

15. Key Countries Market Analysis

    15.1. USA

        15.1.1. Pricing Analysis

        15.1.2. Market Share Analysis, 2022

            15.1.2.1. By Component

            15.1.2.2. By Application

    15.2. Canada

        15.2.1. Pricing Analysis

        15.2.2. Market Share Analysis, 2022

            15.2.2.1. By Component

            15.2.2.2. By Application

    15.3. Brazil

        15.3.1. Pricing Analysis

        15.3.2. Market Share Analysis, 2022

            15.3.2.1. By Component

            15.3.2.2. By Application

    15.4. Mexico

        15.4.1. Pricing Analysis

        15.4.2. Market Share Analysis, 2022

            15.4.2.1. By Component

            15.4.2.2. By Application

    15.5. Germany

        15.5.1. Pricing Analysis

        15.5.2. Market Share Analysis, 2022

            15.5.2.1. By Component

            15.5.2.2. By Application

    15.6. UK

        15.6.1. Pricing Analysis

        15.6.2. Market Share Analysis, 2022

            15.6.2.1. By Component

            15.6.2.2. By Application

    15.7. France

        15.7.1. Pricing Analysis

        15.7.2. Market Share Analysis, 2022

            15.7.2.1. By Component

            15.7.2.2. By Application

    15.8. Spain

        15.8.1. Pricing Analysis

        15.8.2. Market Share Analysis, 2022

            15.8.2.1. By Component

            15.8.2.2. By Application

    15.9. Italy

        15.9.1. Pricing Analysis

        15.9.2. Market Share Analysis, 2022

            15.9.2.1. By Component

            15.9.2.2. By Application

    15.10. India

        15.10.1. Pricing Analysis

        15.10.2. Market Share Analysis, 2022

            15.10.2.1. By Component

            15.10.2.2. By Application

    15.11. Malaysia

        15.11.1. Pricing Analysis

        15.11.2. Market Share Analysis, 2022

            15.11.2.1. By Component

            15.11.2.2. By Application

    15.12. Singapore

        15.12.1. Pricing Analysis

        15.12.2. Market Share Analysis, 2022

            15.12.2.1. By Component

            15.12.2.2. By Application

    15.13. Thailand

        15.13.1. Pricing Analysis

        15.13.2. Market Share Analysis, 2022

            15.13.2.1. By Component

            15.13.2.2. By Application

    15.14. China

        15.14.1. Pricing Analysis

        15.14.2. Market Share Analysis, 2022

            15.14.2.1. By Component

            15.14.2.2. By Application

    15.15. Japan

        15.15.1. Pricing Analysis

        15.15.2. Market Share Analysis, 2022

            15.15.2.1. By Component

            15.15.2.2. By Application

    15.16. South Korea

        15.16.1. Pricing Analysis

        15.16.2. Market Share Analysis, 2022

            15.16.2.1. By Component

            15.16.2.2. By Application

    15.17. Australia

        15.17.1. Pricing Analysis

        15.17.2. Market Share Analysis, 2022

            15.17.2.1. By Component

            15.17.2.2. By Application

    15.18. New Zealand

        15.18.1. Pricing Analysis

        15.18.2. Market Share Analysis, 2022

            15.18.2.1. By Component

            15.18.2.2. By Application

    15.19. GCC Countries

        15.19.1. Pricing Analysis

        15.19.2. Market Share Analysis, 2022

            15.19.2.1. By Component

            15.19.2.2. By Application

    15.20. South Africa

        15.20.1. Pricing Analysis

        15.20.2. Market Share Analysis, 2022

            15.20.2.1. By Component

            15.20.2.2. By Application

    15.21. Israel

        15.21.1. Pricing Analysis

        15.21.2. Market Share Analysis, 2022

            15.21.2.1. By Component

            15.21.2.2. By Application

16. Market Structure Analysis

    16.1. Competition Dashboard

    16.2. Competition Benchmarking

    16.3. Market Share Analysis of Top Players

        16.3.1. By Regional

        16.3.2. By Component

        16.3.3. By Application

17. Competition Analysis

    17.1. Competition Deep Dive

        17.1.1. Amazon Web Services

            17.1.1.1. Overview

            17.1.1.2. Product Portfolio

            17.1.1.3. Profitability by Market Segments

            17.1.1.4. Sales Footprint

            17.1.1.5. Strategy Overview

                17.1.1.5.1. Marketing Strategy

        17.1.2. Cisco Systems, Inc.

            17.1.2.1. Overview

            17.1.2.2. Product Portfolio

            17.1.2.3. Profitability by Market Segments

            17.1.2.4. Sales Footprint

            17.1.2.5. Strategy Overview

                17.1.2.5.1. Marketing Strategy

        17.1.3. Cloudera, Inc.

            17.1.3.1. Overview

            17.1.3.2. Product Portfolio

            17.1.3.3. Profitability by Market Segments

            17.1.3.4. Sales Footprint

            17.1.3.5. Strategy Overview

                17.1.3.5.1. Marketing Strategy

        17.1.4. Hitachi Data Systems

            17.1.4.1. Overview

            17.1.4.2. Product Portfolio

            17.1.4.3. Profitability by Market Segments

            17.1.4.4. Sales Footprint

            17.1.4.5. Strategy Overview

                17.1.4.5.1. Marketing Strategy

        17.1.5. Datameer, Inc.

            17.1.5.1. Overview

            17.1.5.2. Product Portfolio

            17.1.5.3. Profitability by Market Segments

            17.1.5.4. Sales Footprint

            17.1.5.5. Strategy Overview

                17.1.5.5.1. Marketing Strategy

        17.1.6. Fair Isaac Corporation

            17.1.6.1. Overview

            17.1.6.2. Product Portfolio

            17.1.6.3. Profitability by Market Segments

            17.1.6.4. Sales Footprint

            17.1.6.5. Strategy Overview

                17.1.6.5.1. Marketing Strategy

        17.1.7. MapR Technologies

            17.1.7.1. Overview

            17.1.7.2. Product Portfolio

            17.1.7.3. Profitability by Market Segments

            17.1.7.4. Sales Footprint

            17.1.7.5. Strategy Overview

                17.1.7.5.1. Marketing Strategy

        17.1.8. MarkLogic

            17.1.8.1. Overview

            17.1.8.2. Product Portfolio

            17.1.8.3. Profitability by Market Segments

            17.1.8.4. Sales Footprint

            17.1.8.5. Strategy Overview

                17.1.8.5.1. Marketing Strategy

        17.1.9. Microsoft Corporation

            17.1.9.1. Overview

            17.1.9.2. Product Portfolio

            17.1.9.3. Profitability by Market Segments

            17.1.9.4. Sales Footprint

            17.1.9.5. Strategy Overview

                17.1.9.5.1. Marketing Strategy

        17.1.10. Teradata Corporation.

            17.1.10.1. Overview

            17.1.10.2. Product Portfolio

            17.1.10.3. Profitability by Market Segments

            17.1.10.4. Sales Footprint

            17.1.10.5. Strategy Overview

                17.1.10.5.1. Marketing Strategy

18. Assumptions & Acronyms Used

19. Research Methodology

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