Hadoop Benchmark: Cloudera vs. Hortonworks vs. MapR
Comparing the top Hadoop distributions
The Hadoop Wars: Cloudera and Hortonworks’ Death Match for Mindshare
source L http://www.experfy.com/blog/cloudera-vs-hortonworks-comparing-hadoop-distributions/
Comparing top three Hadoop distributions: Cloudera vs Hortonworks 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
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.
Cloudera Overview
Hortonworks
Hortonworks, founded in 2011, has quickly emerged as one of the leading vendors of Hadoop. The distribution provides open source platform based on Apache Hadoop for analysing, storing and managing big data. Hortonworks is the only commercial vendor to distribute complete open source Apache Hadoop without additional proprietary software. Hortonworks’ distribution HDP2.0 can be directly downloaded from their website free of cost and is easy to install. The engineers of Hortonworks are behind most of Hadoop’s recent innovations including Yarn, which is better than MapReduce in the sense that it will enable inclusion of more data processing frameworks.
No comments:
Post a Comment