Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: How MapR’s M7 Platform Improves NoSQL and Hadoop
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > How MapR’s M7 Platform Improves NoSQL and Hadoop
AnalyticsBig DataBusiness IntelligenceData MiningData QualityData VisualizationData WarehousingHadoopHardwareITLocationMapReduceOpen SourceSecuritySocial DataSoftwareSQLUnstructured DataWorkforce Data

How MapR’s M7 Platform Improves NoSQL and Hadoop

MicheleNemschoff
MicheleNemschoff
5 Min Read
Image
SHARE

ImageThe M7 Edition. Sounds like a high performance sports car, doesn’t it?

ImageThe M7 Edition. Sounds like a high performance sports car, doesn’t it? In reality, M7 is MapR’s enterprise-grade platform that provides its own unique brand of high-performance, dependability and ease of use to both NoSQL and Hadoop applications. M7 removes the trade-offs organizations typically face when looking to deploy a NoSQL solution. Here’s a look at how the M7 platform is making NoSQL and Hadoop easier, faster and more dependable.


Easier

More Read

Predictive Analytics Conference Program: PAW – Oct 20-21
Amazon: Using Big Data Analytics to Read Your Mind
How To Develop A Top-Notch Data Warehousing System
10 of the Top Marketing BI Software Options
Technology Change Reaps Rewards

Since enterprises already have several disparate data systems, having the ability to unify NoSQL and Hadoop under a single scalable cluster eliminates data silos and provides administrative simplicity.


The M7 Edition works smoothly in delivering greater performance without the need for compactions or consistency checks that other distributions require. In addition, M7 is said to eliminate RegionServers, additional processes, or any redundant layers between the application and the clustered data. And with a simplified architecture, M7 features zero NoSQL administration by eliminating manual operations related to HBase administration. This is accomplished through automated operations such as region splits and self-tuning.


Additionally, M7 works with standard Apache HBase API’s, making it a easy to adopt.


Faster

As for being fast, MapR claims that M7 “delivers performance of over one million operations/sec with a ten-node cluster that can scale linearly.” And speaking of scalability, M7 is said to be capable of supporting “up to one trillion tables across thousands of nodes.” Additionally, according to MapR, “M7 provides consistent low latency by avoiding garbage collections or compactions that affect performance. Low disk I/O coupled with smaller disk footprint makes database operations on disk fast and predictable.”


More Dependable

In terms of reliability and dependability, M7 is said to provide “instant recovery from failures, ensuring 99.999% availability for Apache HBase and Hadoop applications.” Unlike other Hadoop distributions running HBase, which often require a good half-hour or more of downtime to reassign a region when a node goes down, M7 facilitates instant recovery from data replicated in the cluster. In fact, with M7 apparently there is no downtime required for any operation, even schema changes.

Another important aspect of dependability is data protection, and M7 provides full protection for NoSQL applications, Apache HBase applications included. M7’s expanded Snapshots protect against user or application errors by enabling “point-in-time” recovery, not just of tables, but all data, including both files and tables. And while downtime is required to restore HBase tables in other distributions, M7 allows data to be read and recovered directly from Snapshots with no downtime.

The main benefit of the M7 platform in making NoSQL and Hadoop easier, faster and more dependable is that it makes information easier to consume while simplifying queries. This is big for organizations looking to leverage their big data through analytics. Commenting on this point on the MapR website, John Schroeder, MapR’s co-founder and CEO recently stated, “Our customers are moving Hadoop from pilot adoption and project use to mainstream enterprise deployments.” Schroeder goes on to say that, “MapR customers are experiencing the same reliability and enterprise-level performance with our distribution as they have seen with the Oracle platform at a fraction of the cost.”

NOTE: Industry experts point out that the learning curve associated with the Hadoop platform continues to be a barrier to implementation for organizations. In an effort to shorten the learning curve, Robert D. Schneider—the author of Hadoop for Dummies—has released an eBook entitled the Hadoop Buyer’s Guide. In the guide, sponsored by Ubuntu, the author provides a good overview of what Hadoop is and what it does—all good information that will help readers better understand what’s going on with Big Data, MapReduce and Hadoop.

To download the free eBook go to Hadoopbuyersguide.com.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Internet connection tips for big data
Big Data

Invaluable Tips for Selecting Internet Service in the Age of Big Data

9 Min Read

Wedding Bells: Risk Management and Performance Management

3 Min Read

Prototyping Cloud Analytic Applications

4 Min Read

What Were They Thinking?

3 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?