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28th September 2020, Monday
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Comparison AWS Data Lake 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