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DBMS > Cubrid vs. Netezza vs. Prometheus vs. Spark SQL

System Properties Comparison Cubrid vs. Netezza vs. Prometheus vs. Spark SQL

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPData warehouse and analytics appliance part of IBM PureSystemsOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecubrid.com (korean)
cubrid.org (english)
www.ibm.com/­products/­netezzaprometheus.iospark.apache.org/­sql
Technical documentationcubrid.org/­manualsprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCUBRID Corporation, CUBRID FoundationIBMApache Software Foundation
Initial release2008200020152014
Current release11.0, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaGoScala
Server operating systemsLinux
Windows
Linux infoincluded in applianceLinux
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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 infoImport of XML data possibleno
Secondary indexesyesyesnono
SQL infoSupport of SQLyesyesnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
OLE DB
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresyesnono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationyes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencynone
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptnono

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More resources
CubridNetezza infoAlso called PureData System for Analytics by IBMPrometheusSpark SQL
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