A peep into the world of top hadoop distributions

A Peep into the World of Top Hadoop Distributions

Hadoop has taken rapid strides in this world ridden with Big Data technology, predictive analysis tactics, and open source codes. This open source project has been taken up by numerous vendors who have been developing their own distributions, improving upon its code base, or adding new functionalities. Read on for more insights on the major distributions of Hadoop and how they are different from its standard edition. 

Features of Apache Hadoop

Before moving ahead with the stack of top Hadoop distributions, take a look at what a standardized open sourced Hadoop distribution includes:

  • Hadoop Distributed File System (HDFS)
  • Hadoop MapReduce frameworks for operating computations in parallel
  • Hadoop Common, set of important utilities and libraries used by diverse Hadoop modules

These are the features of the basic kind of Hadoop components; you will find other solutions too. These include Apache Pig, Apache Hive, Apache Zookeeper, etc., and are used for solving specific tasks, speeding up computations, optimizing routine tasks, and so forth. 

Vendor Distributions: Focus and Features

Hadoop linked vendor distributions are specifically designed for overcoming issues that plague the open source edition and for providing additional value to all customers. They focus on: 

Reliability

These distributions have faster reactions to bug detection and promptly deliver patches and fixes; thereby offering more reliable services at all times. 

Support

Hadoop vendors are now providing technical assistance that’s making it possible for organizations to adopt more robust platforms for enterprise-grade and mission-critical tasks.

Completeness

Diverse Hadoop distributions are now coming into the fray and are appropriately supplementing other tools for addressing specific tasks.

Growth

Vendors participating in the efforts of improving standard Hadoop distributions are giving back updated codes to the repository, thereby fostering the overall growth of the open-source community.

Top Hadoop Distributions Competing with Big Data Analytics

Cloudera, Hortonworks and MapR—these are the 3 top Hadoop distributions grabbing a larger percentage of the market. While MapR is adding certain proprietary components to M3, M5, and M7 distributions for improving upon the Hadoop framework’s performance and stability, Hortonworks and Cloudera claim to be 100% open source in nature. 

Along with these, there are more Hadoop distributions available from Pivotal Software, IBM, Intel, and others. They may serve as important parts of software suite or customized to specific tasks; for instance, Intel’s distribution that’s optimized for performing along with Xeon microprocessor.

Popular Hadoop Distributions and their Key Features

Cloudera
 

  • Deployment, Management & Configuration 
  • Hadoop readiness checks and automated deployment
  • Ensures optimal settings and installs the complete CDH stack quickly


Service Management

  • Configures and manages all the CDH services, including Search and Impala, from a defined central interface

Security Management

  • Ensures optimum security across the data cluster and includes Kerberos authentication as well as role-based administration

Resource Management

Allocates cluster resources via workloads or through application/user/group for eliminating contention and ensuring Quality-of-Service (QoS)

High Availability

Easy to configure and manage Cloudera is freely available for services such as HDFS, YARN, HBase, MapReduce and Oozie

Hortonworks

For Hadoop operators

  • Smart configuration that brings new user experiences that’s opinionated, guided, and more digestible to aid configuration of HDFS, HBase, YARN, and Hive.
  • Customized dashboards and configured for shared access to large-sized clusters with the help of easy-to-use web interfaces, with total compatibility with the YARN Capacity Scheduler.

For Hadoop developers

  • SQL Editor for usage with Hive.
  • Integrated features that allow for displaying visual “explain plans”, SQL query building, and extended debugging experiences.
  • Easy Pig editorial features and web-centric HDFS browser.
  • New user experiences with Apache Falcon.
  • Web-forms based approach for rapid development of processes and feeds. 

MapR

  • Complete Hadoop distribution that includes Hive, Pig, Mahout, Apache HBase, and the other components of the Apache Hadoop ecosystem
  • 24x7 access to NoSQL applications for developing operational database applications with zero downtime on the high-performance Hadoop platform. 
  • Simplified design MapReduce workloads with database workloads, and workflows with unified namespaces for tables and files.
  • MapR offers POSIX-compliant read-write file systems for mounting the cluster via NFS. This allows direct streaming of data by applications and enabling existing C/C++ libraries/file-based applications to develop read-write operations on the clustered data. 

Way Forward

 “Big data analytics and the Apache Hadoop open source project are rapidly emerging as the preferred Big Data solutions to address business and technology trends that are disrupting traditional data management and processing,” once said Marcus Collins, research analyst at Gartner. In current times, Hadoop distributions are providing open-source technology solutions with increasing scalability, fast big data analytics, less expensive storage systems, and economical server costs in place. 

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