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The Big Data Hadoop Market Overview and Why MapR Is A Leader


Guest Post from Michele Nemschoff, VP Corporate Marketing, MapR


MapR announced this week that they were among the select companies that Forrester Research Inc. invited to participate in its February 2014 report entitled The Forrester Wave™: Big Data Hadoop Solutions, Q1 2014. MapR was cited as a Leader, and achieved the highest score for Current Offering among all reviewed vendors in the report. The overall score for MapR in the “Current Offering” division was 4.25 out of 5, which was the highest score out of the nine included vendors.


Our Response to the Results:


So what makes our product offering stand out above the rest? To understand our advantages more clearly, let’s begin by looking at the current state of the Hadoop market.


Generally speaking, Hadoop distributions fall into two different roles. Dan Woods described these roles in detail in his article A Quick Guide To Choosing The Right Way To Use Hadoop. Let’s take a brief look at the two of them:


  • Completers create enhancements to complete missing pieces in the Hadoop structure that the open source community can’t provide.
  • Builders focus on extending and improving upon the existing open source project. They share the work among all Hadoop users to make it fundamentally stronger.




Completers view Hadoop as a magnificent work in progress. They work to fill specific needs that are necessary for specific market demands. Instead of depending on the open source builders to identify and fix every problem, they take it upon themselves to invest large amounts of resources into fixing these problems with precision and efficiency.


Completers take credit for the creation of administrative, management and product monitoring tools that have made working with Hadoop easier. MapR is currently considered the leader of all completers. In terms of the amount of enhancements made to Hadoop, we have added far and above the largest amount of value.




Builders dedicate resources to improving the open source project. This large community of developers are not answerable to a central leadership, and they are funded by the community at large. With over 60 updates to the open source project since its creation in 2005, it is clear that this network of builders is driving important innovation.


Another job for many builders is teaching. Distributions centered around “building” offer services that teach clients how to utilize Hadoop to its greatest capacity. This increases Hadoop’s market value and provides more resources to the building of its infrastructure.


MapR is also a member of this builder community and we have worked diligently to strengthen the core project for our clients. We ensure binary level compatibility with all open source Apache projects. We have made significant contributions to Hadoop projects such as Apache Mahout and Apache Drill. MapR adds additional compatibility with its distributed NFS service, which can be used to expose MapR-hosted data to other kinds of Hadoop clusters by using the local file interface.


About Our Current Product Offering


The MapR M7 Enterprise Database Edition is our most robust product offering. This edition includes five key features that make it far more enterprise-grade than any other Hadoop distribution.


Zero Downtime

MapR M7 boasts true High Availability. We eliminated the single point-of-failure with the use of Self-Healing HA, JobTracker HA and NFS HA. Redundant servers take over when a node fails without any lag times. There is also no additional configuration needed to take advantage of full disaster recovery with remote site mirroring technology. Finally, point-in-time recovery snapshots include all files and tables (not just the closed ones).


Zero Database Administration

With MapR M7, there is no extra server administration required and no manual optimizations to schedule or perform. MapR M7 is self-optimizing and doesn’t require embedding low-level administrative code, unlike many other Hadoop databases.


Integrated Security

Access Control Expressions grant permissions at the table, column family and column level by a combination of user, group and role. MapR M7 is also integrated with Kerberos and Linux PAM modules, and leverages standard NSA Suite B cryptography by supporting native authentication.


High Throughput

MapR M7 runs over 30,000 batch put operations per second on one node, and shows as much as a 10-fold speed improvement over HBase.


Extreme Scalability

MapR M7 can scale to an unlimited number of tables; 64 column families per table; an unlimited number of columns, and cell sizes of up to 16 MB.


Download the M7 datasheet here.


How MapR Scored


In the aforementioned Forrester Wave™ report, researchers evaluated the Current Offering in four different sub-categories, and graded each on a scale of one to five, with one being weak five being strong. Take a look at the MapR scores:




Data and Processing


Setup, Management and Monitoring Tools


Hadoop Compatibility and Community


Current Offering Score


“We believe this report is a great acknowledgement of how MapR is serving the enterprise market to help ensure production success," said Jack Norris, chief marketing officer, MapR Technologies. "MapR is working with customers around the world on enterprise Hadoop deployments to transform their business and gain measurable competitive advantage.”


We are excited to have MapR recognized as a leader in this big data Hadoop evaluation. Our team continues to strive for industry excellence, bringing unprecedented dependability, ease-of-use and world-record speed to Hadoop.


Senior Manager, Cloud Online Marketing
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About the Author


I manage the HPE Helion social media and website teams promoting the enterprise cloud solutions at HPE for hybrid, public, and private clouds. I was previously at Dell promoting their Cloud solutions and was the open source community manager for OpenStack and at Rackspace and Citrix Systems. While at Citrix Systems, I founded the Citrix Developer Network, developed global alliance and licensing programs, and even once added audio to the DOS ICA client with assembler. Follow me at @SpectorID

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