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DBMS > Citus vs. Cubrid vs. HarperDB vs. Spark SQL vs. Transbase

System Properties Comparison Citus vs. Cubrid vs. HarperDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonCubrid  Xexclude from comparisonHarperDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Spark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMSRelational DBMS
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
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.citusdata.comcubrid.com (korean)
cubrid.org (english)
www.harperdb.iospark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.citusdata.comcubrid.org/­manualsdocs.harperdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperCUBRID Corporation, CUBRID FoundationHarperDBApache Software FoundationTransaction Software GmbH
Initial release20102008201720141987
Current release8.1, December 201811.0, January 20213.1, August 20213.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, C++, JavaNode.jsScalaC and C++
Server operating systemsLinuxLinux
Windows
Linux
OS X
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesdynamic schemayesyes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyesyes
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 functionalitynononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyesSQL-like data manipulation statementsSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java Stored ProceduresCustom Functions infosince release 3.1noyes
Triggersyesyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneA table resides as a whole on one (or more) nodes in a clusteryes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyes infothe nodes on which a table resides can be definednoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic execution of specific operationsnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and rolesnofine grained access rights according to SQL-standard

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More resources
CitusCubridHarperDBSpark SQLTransbase
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