Top Ten Difference Between Hadoop One and Hadoop Two

Top Ten Difference Between Hadoop One Hadoop Two

S.No Hadoop 1.X Hadoop 2.X
1 Hadoop 1.x having only two components for processing the data that two components are HDFS and MapReduce. Hadoop 2.x having three components for processing the data that three components are HDFS,MapReduce and Yarn.
2 Hadoop 1.x supports mapreduce tools and distributed models only but not support non mapreduce tools. It allows Mapreduce tools and other types of tools and distibuted models like Hbase,Spark.
3 In Hadoop 1.x Mapreduce does clustering and resource management Process. In Hadoop 2.x YARN does clustering and resource management Process.
4 Hadoop 1.x have only 4000 nodes per cluster. Hadoop 2.x have 10000 nodes per cluster.
5 Hadoop 1.x works on slot which run only map tasks or reduce tasks. Hadoop 2.x works on containers which runs on all generic tasks.
6 Hadoop 1.x having one name node to manage entire namespaces. Hadoop 2.x having multiple name node to manage multiple namespaces.
7 If namenode failure on hadoop one it needs manual work to overcome the failure. If namenode failure on hadoop two, it configured to automatic recovery options.
8 Hadoop 1.x does not support windows. It supports windows.
9 Namenode failure affects the whole hadoop 1.x stack. In Hadoop 2.x hbase,pig are handles the namenode failure.
10 Hadoop 1.x not support data streaming and real time data processing. It support data streaming and real time data processing.

 

Also Read – Top Ten Difference Between Apache Hbase and Hive

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