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Hadoop-as-a-Service (HaaS) Market
Global Hadoop-as-a-Service (HaaS) Market (Deployment Types, End User and Geography) - Size, Share, Global Trends, Company Profiles, Demand, Insights, Analysis, Research, Report, Opportunities, Segmentation and Forecast, 2013 - 2020
Published: Aug-2014    |    Formats: PDF & Excel   |   Author(s):Ranjan Singh   |   Code: IC 14489
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Pages 145
Tables 42

Hadoop-as-a-Service (HaaS/HDaaS), is a novel term that defines virtual storage and analysis of data on the cloud. Also termed as “hadoop in the cloud,” HaaS has emerged as a replacement to On-premises hadoop. It comprises of data storage in the cloud and its analysis through hadoop without the need to install any infrastructure in the premises. HaaS market has witnessed a tremendous growth in 2013 and has doubled from the market size in 2012. HaaS market is evolving and current users include SaaS providers, social media companies, and gaming companies. The technology is yet to enter into the mainstream commercial market. However, it is expected to witness a tremendous growth in the next 7 years, expanding its horizon into the end user industries of conventional hadoop.

Amazon Web Services (AWS) holds lion’s share in the market, holding nearly 90% of the global market. Amazon Elastic MapReduce (EMR) is the HaaS service by AWS. It provides hadoop based platform for data analysis with S3 as the storage system and EC2 as the compute system. Microsoft HDInsight, Cloudera CDH3, IBM Infoshpere BigInsights, EMC GreenPlum HD and Windows Azure HDInsight Service are the primary HaaS services by global IT giants. Altiscale is another player in the market with a comparatively minimal share in the market; however, holds potential to compete with the existing companies. Altiscale and Quobole are the two managed or Pure Play HaaS providers. Contrary to AWS, they provide complete running and management of the hadoop jobs.

Global HaaS market is segmented into Pure Play and Run It Yourself based on deployment options available to the customers. Run IT Yourself (RIY) type of deployment is the most prominently used service in the current scenario. Further, the market is analyzed and estimated based on regions such as North America, Asia Pacific, Europe and LAMEA. North America is the leading region followed by Europe and Asia Pacific in the overall HaaS market.

Hadoop-as-a-Service (HaaS)


  • Analysis of the Hadoop-as-a-Service market segmented into deployment types, end users and geography is expounded in the report
  • Identification of the various factors that are enhancing and restraining adoption of cloud based hadoop would help the market players in understanding the current market scenario and future prospects
  • Qualitative as well as quantitative analysis of the current market scenario coupled with future estimations through 2014-2020 would help stakeholders take strategic, actionable and profitable decisions
  • Strategic analysis of future prospects of HaaS in Asia Pacific would assist in taking region specific decisions   
  • Porter’s five forces model helps to understand the bargaining power of buyers and suppliers and threat of the new entrants
  • Identification and analysis of the captivating strategies adopted by key market players such as Amazon Web Services, Microsoft, IBM, EMC Corp., Altiscale and others is conducted, which would assist the stakeholders to gain competitive advantages


Hadoop-as-a-Service market is segmented based on deployment types, end users and geography


  • Run It Yourself (RIY)
  • Pure Play (PP)


  • Manufacturing Industry
  • BFSI    
  • Retail Industry    
  • Telecommunications Industry    
  • Healthcare Industry    
  • Government Sector    
  • Media & Entertainment    
  • Trade & Transportation    
  • IT & ITES


  • North America
    • North America end user market
    • Manufacturing Industry
    • BFSI    
    • Retail Industry    
    • Telecommunications Industry    
    • Healthcare Industry    
    • Government Sector    
    • Media & Entertainment    
    • Trade & Transportation    
    • IT & ITES
  • Europe
    • Europe end user market
    • Manufacturing Industry
    • BFSI    
    • Retail Industry    
    • Telecommunications Industry    
    • Healthcare Industry    
    • Government Sector    
    • Media & Entertainment    
    • Trade & Transportation    
    • IT & ITES
  • Asia Pacific
    • Asia Pacific end user market
    • Manufacturing Industry
    • BFSI    
    • Retail Industry    
    • Telecommunications Industry    
    • Healthcare Industry    
    • Government Sector    
    • Media & Entertainment    
    • Trade & Transportation    
    • IT & ITES
    • LAMEA end user market
    • Manufacturing Industry
    • BFSI    
    • Retail Industry    
    • Telecommunications Industry    
    • Healthcare Industry    
    • Government Sector    
    • Media & Entertainment    
    • Trade & Transportation    
    • IT & ITES 



1.1 Report Description
1.2 Reason for doing the study
1.3 Key Benefits
1.4 Key Market Segments
1.5 Key Audiences
1.6 Research Methodology

1.6.1 Secondary research
1.6.2 Primary research
1.6.3 Analyst tools and models


2.1 CXO Perspective


3.1.1 Moderate growth scenario
3.1.2 Rapid growth scenario
3.1.3 Diminishing growth scenario


4.1 Market Definition and Scope
4.2 Hadoop – An Introduction
4.3 Apache Hadoop – Evolution
4.4 Big data current market scenario
4.5 Defining HaaS – Clearing the Cloud
4.6 Real-time processing/analytics and HaaS
4.7 Proprietary Vs Open Source Hadoop - Where is the future for vendors?

4.7.1 Pros and Cons of Proprietary and Open Source Hadoop - Vendor Perspective Open-Source Hadoop – Pros and Cons Proprietary Hadoop – Pros and Cons

4.8 Elastic Map Reduce (EMR) - HaaS by Amazon Web Services
4.9 On-Premises Hadoop Cluster and Amazon EMR – Case Study
4.10 Hadoop Ecosystem
4.11 Key needs of the customers from HaaS providers
4.12 Hadoop as a Service by - global leaders
4.13 Why Hadoop-as-a-Service?

4.13.1 HaaS: Key Benefits for enterprises

4.14 Hadoop-as-a-Service - Pricing Models

4.14.1 Freemium
4.14.2 Pay-per-use
4.14.3 Subscription based

4.15 Monetizing model implemented by HaaS providers

4.15.1 Per node cost
4.15.2 MapReduce cost
4.15.3 Software usage per hour
4.15.4 Storage cost
4.15.5 Data Transfer cost
4.15.6 Processing cost

4.16 Hadoop Distributed File System
4.17 Future of HaaS in Asia Pacific
4.18 Key findings

4.18.1 Top Factors Hadoop as a service market market
4.18.2 Top Investment Pockets
4.18.3 Top winning strategies

4.19 Porter’s five force analysis

4.19.1 Higher switching cost raises the power of suppliers
4.19.2 Differentiation in products lowers the buyer power
4.19.3 Significant brand loyalty decreases the rivalry
4.19.4 Threat of new entrants is high as location is not an issue
4.19.5 Threat of internal substitution is moderate and complete HaaS substitution is low

4.20 Case Studies
4.21 Market Dynamics

4.21.1 Drivers Increasing competition in the business environment Extremely low upfront costs compared to on-premises Hadoop Growing demand from SMEs Flexibility and Agility for businesses Need for technical expertise and complexity reduction Dropping price of cloud services

4.21.2 Restraints Data Privacy Lack of maturity of hadoop and awareness among consumers

4.21.3 Opportunities Partnerships and fundings taking place in Hadoop Market Rise in consumer awareness


5.1 Run-it-Yourself (RIY)

5.1.1 Key Trends
5.1.2 Competitive Scenario
5.1.3 Market Size

5.2 Pure Play/Managed HaaS

5.2.1 Key Trends
5.2.2 Competitive Scenario
5.2.3 Market Size


6.1 Manufacturing Industry
6.2 BFSI
6.3 Retail Industry
6.4 Telecommunications Industry
6.5 Healthcare Industry
6.6 Government Sector
6.7 Media & Entertainment
6.8 Trade & Transportation
6.9 IT & ITES


7.1 North America

7.1.1 HaaS End User Market Size

7.2 Europe

7.2.1 HaaS End User Market Size  

7.3 Asia Pacific

7.3.1 HaaS End User Market Size


7.4.1 Market Size


8.1 Microsoft Corporation

8.1.1 Company overview
8.1.2 Company snapshot
8.1.3 Business performance
8.1.4 Strategic moves and developments

8.2 IBM Corp.

8.2.1 Company overview
8.2.2 Company snapshot
8.2.3 Business performance
8.2.4 Strategic moves and developments

8.3 Amazon Web Services

8.3.1 Company overview
8.3.2 Company snapshot
8.3.3 Business performance
8.3.4 Strategic moves and developments Principal Strategy: product launch Secondary strategy: partnerships

8.3.5 SWOT analysis & strategic conclusion

8.4 Cloudera, Inc.

8.4.1 Company overview
8.4.2 Company. snapshot
8.4.3 Business performance
8.4.4 Strategic moves and developments Principal Strategy: Partnership Secondary Strategy: Product Launch

8.4.5 SWOT analysis & strategic conclusion

8.5 Hortonworks

8.5.1 Company overview
8.5.2 Company snapshot
8.5.3 Business performance
8.5.4 Strategic moves and developments Principal Strategy:Reseller Agreement Secondary Strategy: Strategic Alliance

8.5.5 SWOT analysis & strategic conclusion


8.6.1 Company overview
8.6.2 Company snapshot
8.6.3 Business performance
8.6.4 Strategic moves and developments Principal Strategy: Product Launch Secondary Strategy: Expansion

8.6.5 SWOT analysis & strategic conclusion

8.7 Emc Corp.

8.7.1 Company overview
8.7.2 Company snapshot
8.7.3 Business performance
8.7.4 Strategic moves and developments
8.7.5 SWOT analysis & strategic conclusion

8.8 Mortar Data Inc.

8.8.1 Company overview
8.8.2 Company snapshot
8.8.3 Business performance
8.8.4 Strategic moves and developments
8.8.5 SWOT analysis & strategic conclusion

8.9 Altiscale

8.9.1 Company overview
8.9.2 Company snapshot
8.9.3 Business performance
8.9.4 Strategic moves and developments
8.9.5 SWOT analysis & strategic conclusion


TABLE 1  HaaS market by geography, base case, 2020 – 2025 ($Million)
TABLE 2  HaaS market by geography, 2020 – 2025 ($Million)
TABLE 3  North America HaaS market by geography, 2020 – 2025 ($Million)
TABLE 4  Hadoop 1.0.3 Patches
TABLE 5  Geographic availability of HDInsight
TABLE 6  List of open source programs used in Hadoop ecosystem
TABLE 7  Global HaaS market by deployment types, 2013 - 2020 ($million)
TABLE 8  Global Run It Yourself HaaS market by geography, 2013 - 2020 ($million)
TABLE 9  Global Pure Play HaaS market by geography, 2013 - 2020 ($million)
TABLE 10  Global HaaS market by End USERS, 2013 - 2020 ($million)
TABLE 11  Global HaaS End USERS market by geography, 2013 - 2020 ($million)
TABLE 12  Global HaaS manufactruring industry by geography, 2013 - 2020 ($million)
TABLE 13  Global HaaS BFSI industry by geography, 2013 - 2020 ($million)
TABLE 14  Global HaaS retail industry by geography, 2013 - 2020 ($million)
TABLE 15  Global HaaS telecommunication industry by geography, 2013 - 2020 ($million)
TABLE 16  Global HaaS healthcare industry by geography, 2013 - 2020 ($million)
TABLE 17  Global HaaS governmnet sector by geography, 2013 - 2020 ($million)
TABLE 18  Global HaaS media & entertainment industry by geography, 2013 - 2020 ($million)
TABLE 19  Global HaaS trade & transportation industry by geography, 2013 - 2020 ($million)
TABLE 20  Global HaaS It & ITES industry by geography, 2013 - 2020 ($million)
TABLE 21  North America HaaS end user market, 2013 – 2020 ($million)
TABLE 22  Europe HaaS end user market, 2013 – 2020 ($million)
TABLE 23  Asia PAcific HaaS end user market, 2013 – 2020 ($million)
TABLE 24  LAMEA HaaS end user market, 2013 – 2020 ($million)
TABLE 25  Snapshot of Microsoft Corporation
TABLE 27  Snapshot of ibm CORP.
TABLE 29  Snapshot of Amazon Web Services
TABLE 39  SNAPSHOT OF mortar data inc.



FIG. 1  HaaS - offered by leading companies
FIG. 2  Top impacting factors (2020 - 2025)
FIG. 3  Top impacting factors, optimistic case (2020 - 2025)
FIG. 4  Top impacting factors, critical case (2020 - 2025)
FIG. 5  Hadoop Ecosystem – Popular tools and core hadoop
FIG. 6  Amazon EMR Work Process
FIG. 7  Bare Metal Hadoop Cluster and Amazon EMR – TCO Comparison
FIG. 8  Bare Metal Hadoop and HaaS – Comparison based on experiment conclusions
FIG. 9  Hadoop Ecosystem
FIG. 10  Big Data Trend – Rise in data  (2005 - 2015)
FIG. 11  Pricing details of Microsoft HDInsight ($, U.S. East)
FIG. 12  Pricing details of Qubole (Hourly Usage)
FIG. 13  Qubole HaaS pricing (Monthly Subscription)
FIG. 14  Few of the Hadoop as a Service Users
FIG. 15  Contribution of SMEs in total GDP of the country (2013)
FIG. 16  Top Factors Impacting HaaS market
FIG. 17  Issues associated with Hadoop (Consumer’s point of view)
FIG. 18  Top investment pockets in HaaS END USER market
FIG. 19  Top winning strategies
FIG. 20  Key Strategies followed by HaaS providers (2012 - 2014)
FIG. 21  key areas of Focus
FIG. 22  Porter’s Five Force Analysis
FIG. 23  Worldwide cloud services revenue by size of enterprises (2012 - 2013)
FIG. 24  Number of cloud price reductions by providers (2013)
FIG. 25  Average size of reduction by service provider (2013)
FIG. 26  Number of reductions by service across major providers (2013)
FIG. 27  HPaaS service by Netflix – An architectural overview
FIG. 28  Big data investments by Industry
FIG. 29  Hadoop Usage Plans in European Organizations
FIG. 30  Geographical location of respondents
FIG. 31  Reasons for low adoption of big data and Hadoop in brazil
FIG. 32  Revenue of microsoft corp. by business segments (2013)
FIG. 33  Revenue of microsoft corp. by business segments (2012)
FIG. 34  Revenue of ibm corp. by business segments (2013)
FIG. 35  Revenue of ibm corp. by business segments (2012)
FIG. 36  Revenue of Amazon from 2010 to 2012
FIG. 37  Revenue of Amazon from U.S. and International business (2010 – 2012)
FIG. 38  Revenue generated by Products and Services for Amazon Web services
FIG. 39  Revenue generated by Products and Services for cloudera,inc
FIG. 40  Revenue generated by Products and Services for HORTONWORKS
FIG. 41  Revenue generated by Products and Services for MAPR TECHNOLOGIES
FIG. 42  Percentage of EMC II revenue (2013, First Quarter)
FIG. 44  Geographical revenue (2013, First Quarter)

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Data scientists and Hadoop providers have yet to reach a consensus regarding the term Hadoop as a Service and what exactly it encompasses. Taking the phrase as-a-service into consideration, HaaS must refer to a service offered by a company wherein hadoop software can be utilized without having to install the infrastructure on the premises. Big data analysis is done through the hadoop platform in the cloud.  The minimum requirement for a service to be considered HaaS is that it should provide a hadoop software platform where data can be fed and analyzed. Infrastructure-as-a-Service offerings that can be utilized by the user to install hadoop should not be considered a HaaS offering. AWS EMR is the most basic type of HaaS offered by companies. If a user employs the AWS EMR service; additional charges (other than the EMR) apply for storage and compute services with S3 and EC2. In such cases, the HaaS revenue generated by the company includes EMR cost, S3 cost and EC2 cost.

HaaS is a novel technology that is yet to enter the mainstream commercial market. HaaS is expected to penetrate the conventional hadoop user base in the coming years. Amazon Web Services is the market leader, holding nearly 90% share of the HaaS market. EMR is a HaaS offering by AWS. Other HaaS offerings include IBM Infosphere BigInsights, Windows Azure HDInsights, and EMC greenplem HD. Altiscale and Quobole are comparatively smaller companies but have come up with a managed hadoop as a service offering which eliminates the need for technical knowledge to run hadoop.

HaaS generated revenue  of around $150 million in 2012. The revenue generated by HaaS has almost doubled from 2012 to 2013. The market is expected to retain its pace throughout 2020. Pure Play HaaS providers are expected to grow at a faster rate, especially in the Asia Pacific region. This is because growing awareness among SMEs in these countries ensures potential customers for HaaS due to its cost competitiveness and due to the growing need for data analytics to sustain in the intensely competitive SME market.


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