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System AllegroGraph Hive
 Name AllegroGraph --
 Version AllegroGraph 6.4.2 [2018-06-18] 3.1.2
 Drawbacks NA Can run only on Hadoop with mapreduce
 Advantages -Database being explicitly pre-structured
-Data to self-define the schema at the time of ingest
-Able to connect concepts, properties, and entities across multiple databases and without further coding to extract new, actionable business insights from your data
A file system can be loaded to a Hive data store AS-IS and can be queried using SQL
 Website www.allegrograph.com,
www.franz.com/agraph/allegrograph
https://hive.apache.org
 Languages Supported Java, Python, Ruby, Perl, C#, Clojure and Common Lisp --
 JSON Support yes yes
 XML Support yes no
 Brief description -Modern, high-performance, persistent graph database
-Uses efficient memory utilization in combination with disk-based storage, enabling it to scale to billions of quads while maintaining superior performance
-Supports SPARQL, RDFS++ and Prolog reasoning from numerous applications
The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive
 Database Model Graph Database, A triplestore or RDF store Tabular Data Model
 Technical Documentation franz.com/agraph/support/documentation/current/agraph-introduction.html --
 License Commercial --
 Cloud-based / SaaS No --
 Implementation Language Common Lisp C,C++
 Operating System Supported Windows, Linux, and Mac OS X Linux, OS X,
 Options for Integration / Access API Java, Python, Common Lisp and other APIs -
 Consistency Yes Highly Consistent
 Foreign Keys No No
 Streaming Support Yes Yes
 Data Storage Schema Yes --
 Analytics Support Yes, AllegroGraph Recognized Among Top 10 Analytics Solution Providers by Pharma Tech Outlook for 2016 --
 Notable Users -- -
 Key Differentiator -- Probably most Widely used reporting database in big data ecosystem . Has a web front end
 Concurrency -- Yes
 Partitioning -- Yes
 Replication -- Yes
 Secondary Indexes -- Yes
 SchemaLess -- --
 SQL Query -- No