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Comparison Hadoop MapR
 Name MapR
 Version Version 6.1
 Drawbacks MapR has done lot of fork on top of Apache products. They even have a MapR filesystem which makes the product quite far from the original apache hadoop distribution.
 Advantages --
 Languages Supported Java Python
 Website www.mapr.com
 XML Support no
 JSON Support yes
 Brief description MapR provides access to a variety of data sources from a single computer cluster including big data workloads such as Apache Hadoop Apache Spark and a distributed file system called MapRFS.
 Database Model Hadoop File System (HDFS)
 Technical Documentation https://mapr.com/docs/61/
 License Commercial
 Cloud-based / SaaS https://mapr.com/products/orbit-cloud/
 Implementation Language NA
 Operating System Supported Linux
 Options for Integration / Access API Restful HTTP
 Consistency NA
 Foreign Keys Not but you can join two files using Hive and Impala
 Streaming Support Yes
 Analytics Support Using Mlib in Apache Spark
 Data Storage Schema Hadoop File System (HDFS)
 Notable Users Dun & Bradstreet AoL
 Key Differentiator NA
 Concurrency Yes
 Partitioning Yes
 Replication Yes
 Secondary Indexes Yes in HBase. Datawarehouse using cloudera is generally built using Hbase. Hbase has secondary indexes
 SchemaLess Yes
 SQL Query No. HiveQL similar to SQL can be used withHive