Individuals interested in harness the potential of Big Data, the perfect answer to them to do so is Hadoop. Apache Hadoop, an open source framework enables us in processing larger datasets by distributing them across many commodity HDFS servers. It thus eliminates any dependencies of having high-end hardware, making the whole process economical for the business to implement it. Organizations of any kind who want to work with Hadoop have come better choices of enterprise versions of Cloudera, MapR or Hortonworks to choose from.
Hadoop in its initial version was just designed as a write-once storage infrastructure but over the years it has evolved from just that to expand beyond mere web indexing capacity to much more. Based on Google’s implementation to the MapReduce model, Hadoop has designed to store / process larger datasets and data being available in more than one computer servers. The Hadoop Distributed File System (HDFS) helps breaking down all the incoming data to store them across multiple nodes, the MapReduce component facilitates parallel processing of data across multiple nodes.
Hadoop is no out of the box solution by any means. To build a truly information driven enterprise, where decisions are taken based on data rather than relying on guess work, Organizations will require data management solution that offers not just data governance but also should be able to manage existing enterprise. There should be seamless integration with the existing enterprise infrastructure as well.
The modular architecture of Hadoop makes it very flexible in adding new functionalities that tends to answer more diverse Big Data tasks. Vendors who have implemented over Hadoop’s open-ended framework, tweaked its code to enhance the existing functionalities. In the process of enhancing features, few of the implementation have concentrated in fixing the existing drawbacks of Apache Hadoop. In the distribution of Hadoop is concerned, there are 3 companies that stand out in the competition, namely Cloudera, MapR and Hortonworks.
Cloudera has been in the field of Hadoop distribution from quite longer than Hortonworks, where Hortonworks joined later. Cloudera and Hortonworks are both 100% pure implementation of same Hadoop core and are open source. Each of these Hadoop distributions have their own pros and cons and it is best understood by making a comparative study of these distributions to understand it better. Let us now get neck deep into the comparative study between these two Hadoop distributions, Cloudera and Hortonworks in detail.
Both of these Hadoop distributions namely Cloudera and Hortonworks provide consulting, training and technical assistance to consumers who are in need. Cloudera has a range of its own proprietary elements tagged with its Hadoop distribution in its Enterprise 4.0 version (addition of administrative and management capabilities to Apache Hadoop core software) whereas Hortonworks’ Hadoop distribution is a pure 100% open source framework for direct usage with no proprietary softwares tagged along with its distribution.
Cloudera Inc. was founded as a collective efforts of big data geniuses from Google, Oracle, Yahoo and Facebook in the year 2008. Cloudera was the first one to develop and distribute Apache Hadoop based software and is still the largest organization with the largest user base with many customers to their belt. In addition to the core of the distribution based upon Apache Hadoop, Cloudera has provided more proprietary tools such as the Cloudera Management suite to automate the installation process, Cloudera Search to ease the process of search of products. The Cloudera Management suite provides the users reduced deployment time, real time node counts etc.
Hortonworks was founded in the year 2011 and has then quickly emerged on the leading vendors to provide Hadoop distributions. The Hadoop distribution made available by Hortonworks is also an open source platform based on Apache Hadoop for analyzing, storage and management of Big Data. Hortonworks is the only vendor to provide a 100% open source distribution of Apache Hadoop with no proprietary softwares tagged with it. Hortonworks distribution, HDP 2.0 can be accessed and downloaded from their organization website for free and its installation process is also very easy. The inclusion on YARN into the Hadoop’s ecosystem from the distribution made available by Hortonworks – makes it better than MapReduce, in a sense to enable more integrations of data processing frameworks.
With the discussions about Cloudera and Hortonworks being done individually, let us now try to understand the similarities that both of these Hadoop distributions share with each other. This will bring in a better sense of understanding about Hadoop as such and what are the pain points that both Cloudera and Hortonworks have tried to address in common that Apache Hadoop missed in its initial versions of it.
1. Both Cloudera and Hortonworks are both built upon the same core of Apache Hadoop, thereby both of these share more similarities than differences between each other.
2. Both Cloudera and Hortonworks are enterprise ready Hadoop distributions to answer customer requirements in regards to Big Data. Each of these have passed the tests of consumers in the areas of security, stability and scalability. They provide paid trainings and services to make ourselves familiarized.
3. Each of Cloudera and Hortonworks have their own established communities that actively help the consumers with their problems.
4. Both of these Hadoop distributions have the Master-Slave architecture
5. Both of these Hadoop distributions have a shared-nothing computing framework
6. Both of these Hadoop distributions have its support towards MapReduce and YARN.
Having discussed more in detail about these two Hadoop distributions individually, now let us take a look at the differences between these two – in order to decide to choose which vendor over the others available in the market today. If we put all the differences together broadly, Cloudera and Hortonworks differ in these following aspects:
|Cloudera announced its long term achievement to be an enterprise data hub thus eliminating the need of a Data Warehouse.||Hortonworks looks forward to firmly provide Hadoop distribution partnering with data warehousing company Teradata, just for this purpose|
|Cloudera CDH can run on Windows server||Hortonworks HDP is a native component on Windows Server. A Hadoop based Hadoop cluster can be deployed on Windows Azure through HDInsight service|
|Cloudera has the proprietary management software called the Cloudera Manager, SQL Queries handling interface called the Impala, Cloudera Search to provide real-time and easy access of products||Hortonworks uses Ambari for management, Stinger for handling queries and Apache Solr for data search. Hence there are no proprietary softwares in its ecosystem.|
|Cloudera with its proprietary softwares in usage, has a commercial license. Cloudera also encourages the usage of its open source projects absolutely free but it doesn’t include Cloudera Manager or any other proprietary softwares in the package||Hortonworks on the other goes by an open source license.|
|Cloudera comes with a 60 days free trial||Hortonworks is completely free, absolutely.|
|Cloudera has been in this market than any other of its counterparts with more than 350 customers.||Hortonworks is catching up the race quite fast and has more innovations in the Hadoop ecosystem than Cloudera in the recent past|
|Cloudera has many enterprise softwares laid over its open source distributions to help the customers with their unique requirements||Hortonworks provides a framework constituting just the open source projects striving to fulfilling all the customer requirements
In this article, we have introduced you the many available Hadoop distribution vendors. Along with it, we also have discussed in great detail about the similarities and differences between these two Hadoop distributions – Cloudera, Hortonworks.
|Big Data On AWS||Informatica Big Data Integration|
|Bigdata Greenplum DBA||Informatica Big Data Edition|
|Hadoop Testing||Apache Mahout|
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