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DBMS > Hive vs. JanusGraph vs. Kinetica vs. RDF4J vs. Splice Machine

System Properties Comparison Hive vs. JanusGraph vs. Kinetica vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Fully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSGraph DBMSRelational DBMSRDF storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitehive.apache.orgjanusgraph.orgwww.kinetica.comrdf4j.orgsplicemachine.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.janusgraph.orgdocs.kinetica.comrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoinitially developed by FacebookLinux Foundation; originally developed as Titan by AureliusKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20122017201220042014
Current release3.1.3, April 20220.6.3, February 20237.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC, C++JavaJava
Server operating systemsAll OS with a Java VMLinux
OS X
Unix
Windows
LinuxLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
Thrift
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
PHP
Python
Clojure
Java
Python
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functionsyesyes infoJava
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)ShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infovia Faunus, a graph analytics enginenonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and rolesUser authentification and security via Rexster Graph ServerAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
HiveJanusGraph infosuccessor of TitanKineticaRDF4J infoformerly known as SesameSplice Machine
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