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22nd September 2020, Tuesday
 
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Comparison Azure Data Lake Hadoop MapR
 Name Azure Data Lake MapR
 Version NA Version 6.1
 Drawbacks NA 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 Develop massively parallel programs with simplicity Debug and optimize your big data programs with ease Enterprise-grade security auditing. Start in seconds scale instantly pay per job. Built on YARN and designed for the Microsoft cloud --
 Languages Supported Java Python Scala Java Python
 Website aws.amazon.com/rds/aurora/ www.mapr.com
 XML Support no no
 JSON Support yes yes
 Brief description Azure Data Lake Stores and analyze petabyte-size files and trillions of objects 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 Relational Database Hadoop File System (HDFS)
 Technical Documentation https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Overview.html https://mapr.com/docs/61/
 License Commercial Commercial
 Cloud-based / SaaS SaaS Service from AWS https://mapr.com/products/orbit-cloud/
 Implementation Language NA NA
 Operating System Supported Not Applicable as its managed by Azure Linux
 Options for Integration / Access API Restful HTTP Restful HTTP
 Consistency NA NA
 Foreign Keys NA Not but you can join two files using Hive and Impala
 Streaming Support Yes Yes
 Analytics Support NA Using Mlib in Apache Spark
 Data Storage Schema NA Hadoop File System (HDFS)
 Notable Users NA Dun & Bradstreet AoL
 Key Differentiator Azure Data Lake is the most stable of all the out of the box data lake solutions in the market as of sep 2018 NA
 Concurrency Yes Yes
 Partitioning No Yes
 Replication Yes Yes
 Secondary Indexes Yes based on secondary indexes using Solr Yes in HBase. Datawarehouse using cloudera is generally built using Hbase. Hbase has secondary indexes
 SchemaLess Yes Yes
 SQL Query NA No. HiveQL similar to SQL can be used withHive