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Comparison Hadoop Cloudera Azure Data Lake
 Version 5.9.x NA
 Name Cloudera Azure Data Lake
 Drawbacks -- NA
 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 Java Python Scala
 Website www.cloudera.com aws.amazon.com/rds/aurora/
 XML Support no no
 JSON Support yes yes
 Brief description Cloudera is a hybrid open-source packaged distribution primarily of Apache Hadoop, Spark, Kafka. The distribution is called CDH (Cloudera Distribution Including Apache Hadoop). It is targeted at enterprise-class deployments of Hadoop platform. Azure Data Lake Stores and analyze petabyte-size files and trillions of objects
 Database Model Hadoop File System (HDFS) Relational Database
 Technical Documentation https://www.cloudera.com/documentation.html https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Overview.html
 License Commercial Commercial
 Cloud-based / SaaS Altus is the cloud offering of Cloudera SaaS Service from AWS
 Implementation Language NA NA
 Operating System Supported Linux Windows Not Applicable as its managed by Azure
 Options for Integration / Access API Restful HTTP Restful HTTP
 Consistency NA NA
 Foreign Keys Not but you can join two files using Hive and Impala NA
 Streaming Support Yes Yes
 Analytics Support Using Mlib in Apache Spark NA
 Data Storage Schema Hadoop File System (HDFS) NA
 Notable Users Dun & Bradstreet, AoL NA
 Key Differentiator Cloudera Navigator provides lineage of the various jobs and data points. Azure Data Lake is the most stable of all the out of the box data lake solutions in the market as of sep 2018
 Concurrency Yes Yes
 Partitioning Yes No
 Replication Yes Yes
 Secondary Indexes Yes in HBase. Datawarehouse using cloudera is generally built using Hbase. Hbase has secondary indexes Yes based on secondary indexes using Solr
 SchemaLess Yes Yes
 SQL Query No. HiveQL similar to SQL can be used withHive NA