Best comparison : Cloudera vs MapR
Best comparison : Cloudera vs MapR : For all those looking to harness the potential of big data, Hadoop is the platform of choice. This open source software framework enables processing of huge data sets by distributing them across commodity servers. Thus, it eliminates dependency on high-end hardware and makes the entire process economical for businesses to implement. All of the big data enterprises today use Apache Hadoop in some way or the other. To simplify working with Hadoop, enterprise versions like Cloudera, MapR and Hortonworks have sprung up.
In its original version, Hadoop was designed as a simple write-once storage infrastructure. But it has evolved through the years to expand beyond mere web indexing capacity. Based on Google’s MapReduce model, Hadoop is designed to store and process large amounts and variety of data that may reside in multiple computer servers.
While Hadoop’s distributed file system (HDFS) helps break down all incoming data and store them across multiple nodes, the MapReduce component facilitates the simultaneous processing of data across multiple nodes.
Hadoop is by no means an out-of-the-box solution. In order to build a truly information- driven enterprise, where decisions are based on data and not guess works, the companies would require a data management solution that not only offers robust data governance, but also is easily manageable and seamlessly integrates with existing enterprise infrastructure.
The flexible, modular architecture of haddoop allows for adding new functionalities for the accomplishment of diverse Big Data tasks. A number of vendors have taken advantage of Hadoop’s open-ended framework and tweaked its codes to change or enhance its functionalities. In the process they have been able to fix some of the inherent drawbacks of Apache Hadoop. So far as Hadoop distribution is concerned, the three companies that really stand out in the completion are: Cloudera, MapR and Hortonworks.
Comparing top three Hadoop distributions: Best comparison : Cloudera vs MapR
Cloudera has been here for the longest time since the creation of Hadoop. Hortonworks came later. While Cloudera and Hortonworks are 100 percent open source, most versions of MapR come with proprietary modules. Each vendor/distribution has its unique strength and weaknesses, each have certain overlapping features as well. If you are looking to make the most of Hadoop’s immense data processing power, it makes sense in making a comparative study in the top three Hadoop distributions.
Cloudera Inc. was founded by big data geniuses from Facebook, Google, Oracle and Yahoo in 2008. It was the first company to develop and distribute Apache Hadoop-based software and still has the largest user base with most number of clients. Although the core of the distribution is based on Apache Hadoop, it also provides a proprietary Cloudera Management Suite to automate the installation process and provide other services to enhance convenience of users which include reducing deployment time, displaying real time nodes’ count, etc.
In its standard, open source edition, Apache Hadoop software comes with a number of restrictions. Vendor distributions are aimed at overcoming the issues that the users typically encounter in the standard editions. Under the free Apache license, all the three distributions provide the users with the updates on core Hadoop software. But when it comes to handpicking any one of them, one should look at the additional value it is providing to the customers in terms of improving the reliability of the system (detecting and fixing bugs etc), providing technical assistance and expanding functionalities.
All three top Hadoop distributions, Cloudera, MapR and Hortonworks offer consulting, training, and technical assistance. But unlike its two rivals, Hortonworks’ distribution is claimed to be 100 percent open source. Cloudera incorporates an array of proprietary elements in its Enterprise 4.0 version, adding layers of administrative and management capabilities to the core Hadoop software.
Going a step further, MapR replaces HDFS component and instead uses its own proprietary file system, called MapRFS. MapRFS helps incorporate enterprise-grade features into Hadoop, enabling more efficient management of data, reliability and most importantly, ease of use. In other worlds, it is more production ready than its other two competitors.
Through a recent partnership with Canonical, the creator of Ubuntu operating system, MapR is offering Hadoop as a default component of Ubuntu operating system. Under the terms of the partnership, MapR’s M3 Edition for Apache Hadoop will be integrated into Ubuntu operating system.
Upto its M3 edition, MapR is free, but the free version lacks some of its proprietary features namely, JobTracker HA, NameNode HA, NFS-HA, Mirroring, Snapshot and few more.