Hadoop Distribution Market Future Scope, Demands and Growth Analysis by Top Key Players: Amazon Web Services (AWS), Cloudera, Cray, Google Cloud Platform, Hortonworks

Global Hadoop Distribution Market Growth Status and Outlook 2018-2023

Hadoop distributions are used to provide scalable, distributed computing against on-premises and cloud-based file store data. Distributions are composed of commercially packaged and supported editions of open-source Apache Hadoop-related projects. Distributions provide access to applications, query/reporting tools, machine learning and data management infrastructure components. First introduced as collections of components for any use case, distributions are now often delivered as part of a specific solution for data lakes, machine learning or other uses. They subsequently grow into additional, expanded roles, competing with both older technologies like database management systems (DBMSs) and newer ones like Apache Spark.

In particular, this report presents the global revenue market share of key companies in Hadoop Distribution business, shared in Chapter 3.

This report presents a comprehensive overview, market shares and growth opportunities of Hadoop Distribution market by product type, application, key companies and key regions.

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Companies Profiled in this report includes: Amazon Web Services (AWS), Cloudera, Cray, Google Cloud Platform, Hortonworks, Huawei, IBM, MapR Technologies, Microsoft, Oracle, Qubole, Seabox, Teradatal, Transwarp

This study considers the Hadoop Distribution value generated from the sales of the following segments:

Segmentation by product type: breakdown data from 2013 to 2018, in Section 2.3; and forecast to 2023 in section 10.7.



Segmentation by application: breakdown data from 2013 to 2018, in Section 2.4; and forecast to 2023 in section 10.8.






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Research objectives

To study and analyze the global Hadoop Distribution market size by key regions/countries, product type and application, history data from 2013 to 2017, and forecast to 2023.
To understand the structure of Hadoop Distribution market by identifying its various subsegments.
Focuses on the key global Hadoop Distribution players, to define, describe and analyze the value, market share, market competition landscape, SWOT analysis and development plans in next few years.
To analyze the Hadoop Distribution with respect to individual growth trends, future prospects, and their contribution to the total market.
To share detailed information about the key factors influencing the growth of the market (growth potential, opportunities, drivers, industry-specific challenges and risks).
To project the size of Hadoop Distribution submarkets, with respect to key regions (along with their respective key countries).
To analyze competitive developments such as expansions, agreements, new product launches and acquisitions in the market.
To strategically profile the key players and comprehensively analyze their growth strategies.

Table of Content:

2018-2023 Global Hadoop Distribution Market Report (Status and Outlook)

1 Scope of the Report

2 Executive Summary

3 Global Hadoop Distribution by Players

4 Hadoop Distribution by Regions

5 Americas


7 Europe

8 Middle East & Africa

9 Market Drivers, Challenges and Trends

10 Global Hadoop Distribution Market Forecast

11 Key Players Analysis

11.1 Amazon Web Services (AWS)

11.1.1 Company Details

11.1.2 Hadoop Distribution Product Offered

11.1.3 Amazon Web Services (AWS) Hadoop Distribution Revenue, Gross Margin and Market Share (2016-2018)

11.1.4 Main Business Overview

11.1.5 Amazon Web Services (AWS) News

11.2 Cloudera

11.2.1 Company Details

11.2.2 Hadoop Distribution Product Offered

11.2.3 Cloudera Hadoop Distribution Revenue, Gross Margin and Market Share (2016-2018)

11.2.4 Main Business Overview

11.2.5 Cloudera News

11.3 Cray

11.3.1 Company Details

11.3.2 Hadoop Distribution Product Offered

11.3.3 Cray Hadoop Distribution Revenue, Gross Margin and Market Share (2016-2018)

11.3.4 Main Business Overview

11.3.5 Cray News

11.4 Google Cloud Platform

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