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DBMS > Apache Phoenix vs. Citus vs. IBM Db2 Event Store vs. RDF4J

System Properties Comparison Apache Phoenix vs. Citus vs. IBM Db2 Event Store vs. RDF4J

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCitus  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLDistributed Event Store optimized for Internet of Things use casesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSRelational DBMSEvent Store
Time Series DBMS
RDF store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitephoenix.apache.orgwww.citusdata.comwww.ibm.com/­products/­db2-event-storerdf4j.org
Technical documentationphoenix.apache.orgdocs.citusdata.comwww.ibm.com/­docs/­en/­db2-event-storerdf4j.org/­documentation
DeveloperApache Software FoundationIBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2014201020172004
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20198.1, December 20182.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availablecommercial infofree developer edition availableOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC and C++Java
Server operating systemsLinux
Unix
Windows
LinuxLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Unix
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesyes infostandard, with numerous extensionsyes infothrough the embedded Spark runtimeno
APIs and other access methodsJDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yesyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensionsActive-active shard replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes 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.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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