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DBMS > Citus vs. HBase vs. Microsoft Azure Table Storage vs. RDF4J

System Properties Comparison Citus vs. HBase vs. Microsoft Azure Table Storage vs. RDF4J

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLWide-column store based on Apache Hadoop and on concepts of BigTableA Wide Column Store for rapid development using massive semi-structured datasetsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSWide column storeWide column storeRDF store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.citusdata.comhbase.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablesrdf4j.org
Technical documentationdocs.citusdata.comhbase.apache.org/­book.htmlrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2010200820122004
Current release8.1, December 20182.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaJava
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
hostedLinux
OS X
Unix
Windows
Data schemeyesschema-free, schema definition possibleschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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.yes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesnonoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnonono
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP API
Thrift
RESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoCoprocessors in Javanoyes
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)optimistic lockingACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights based on private key authentication or shared access signaturesno

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More resources
CitusHBaseMicrosoft Azure Table StorageRDF4J infoformerly known as Sesame
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