Differences between Hadoop distributions Hadoop is a software framework that enables distributed processing of large amounts of data. Hadoop handles data in a reliable, efficient, and scalable way. In addition to Apache Hadoop, cloudera, hortonworks, mapR, huawei,DKhadoop and others all offer their own commercial versions. Commercial distribution boards provide more professional technical support, which is more important for large enterprises. Different distributions have their own characteristics, and this article gives a brief comparison of each distribution. Comparison versions include: DKhadoop, Cloudera, HortonWorks, MAPR, Huawei Hadoop distribution Lent 1, DKhadoop: It effectively integrates all components of the entire HADOOP ecosystem, deeply optimizes, and recompiles into a complete general computing platform for big data with higher performance, realizing the organic coordination of all components. Therefore, COMPARED with open source big data platform, DKH has up to 5 times (maximum) performance improvement in computing performance. DKhadoop simplifies the complex configuration of big data cluster to three types of nodes (master node, management node, and computing node), which greatly simplifies the management operation and maintenance of the cluster and enhances the high availability, maintainability, and stability of the cluster.
Cloudera release: CDH is Cloudera’s Hadoop release, which is fully open source and offers greater compatibility, security, and stability than Apache Hadoop.
Hortonworks releases: Hortonworks’ flagship product is the HortonWorks Data Platform (HDP), which is also 100% open source. The HDP includes stable versions of Apache Hadoop and all key components. Easy to install, HDP includes a modern, intuitive user interface for installation and configuration tools.
4. MAPR distribution: MAPR is available in both free and commercial versions, with reduced functionality in the free version.
5. Huawei Hadoop Distribution: Huawei hadoop builds the HA functions of NameNode, JobTracker, and HiveServer based on the hadoop HA platform developed by Huawei. When a process fails, the system automatically Failover without manual intervention. This is also a minor patch to Hadoop, which is far less thorough than mapR.