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DBMS > Cubrid vs. Netezza vs. Pinecone

System Properties Comparison Cubrid vs. Netezza vs. Pinecone

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPinecone  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 PureSystemsA managed, cloud-native vector database
Primary database modelRelational DBMSRelational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Websitecubrid.com (korean)
cubrid.org (english)
www.ibm.com/­products/­netezzawww.pinecone.io
Technical documentationcubrid.org/­manualsdocs.pinecone.io/­docs/­overview
DeveloperCUBRID Corporation, CUBRID FoundationIBMPinecone Systems, Inc
Initial release200820002019
Current release11.0, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, Java
Server operating systemsLinux
Windows
Linux infoincluded in appliancehosted
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyesString, Number, Boolean
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
Secondary indexesyesyes
SQL infoSupport of SQLyesyesno
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
OLE DB
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Python
Server-side scripts infoStored proceduresJava Stored Proceduresyes
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept

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More resources
CubridNetezza infoAlso called PureData System for Analytics by IBMPinecone
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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