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Comparison Hadoop Hortonworks Azure Data Lake
 Name Hortonworks Azure Data Lake
 Version HDP v3.0 NA
 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.hortonworks.com aws.amazon.com/rds/aurora/
 XML Support no no
 JSON Support yes yes
 Brief description Hortonworks has three interoperable product lines: HDP (based on Apache Hadoop Apache Hive Apache Spark) HDF (based on Apache NiFi Apache Storm, Apache Kafka), and Data Plane Services (based on Apache Atlas and Cloudbreak Azure Data Lake Stores and analyze petabyte-size files and trillions of objects
 Database Model Hadoop File System (HDFS) Relational Database
 Technical Documentation https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.6.5/index.html https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Overview.html
 License Commercial Commercial
 Cloud-based / SaaS Not Available SaaS Service from AWS
 Implementation Language NA NA
 Operating System Supported Linux 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 hotels.com hilton.com NA
 Key Differentiator More suited for platforms based on windows. Azure has a big partnership with hortonworks. 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