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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCitus  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonIBM Db2 Event Store  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 PostgreSQLMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBDistributed Event Store optimized for Internet of Things use cases
Primary database modelRelational DBMSRelational DBMSRelational DBMSEvent Store
Time Series DBMS
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
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Websitephoenix.apache.orgwww.citusdata.comhsqldb.orgwww.ibm.com/­products/­db2-event-store
Technical documentationphoenix.apache.orgdocs.citusdata.comhsqldb.org/­web/­hsqlDocsFrame.htmlwww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software FoundationIBM
Initial release2014201020012017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20198.1, December 20182.7.2, June 20232.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availableOpen Source infobased on BSD licensecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJavaC and C++
Server operating systemsLinux
Unix
Windows
LinuxAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinux infoLinux, macOS, Windows for the developer addition
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes
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 functionalitynono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyes infostandard, with numerous extensionsyesyes infothrough the embedded Spark runtime
APIs and other access methodsJDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API infoJDBC via HTTP
JDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
All languages supporting JDBC/ODBC
Java
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java, SQLyes
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
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 extensionsnoneActive-active shard replication
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 ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
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-standardfine grained access rights according to SQL-standard

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More resources
Apache PhoenixCitusHyperSQL infoalso known as HSQLDBIBM Db2 Event Store
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