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DBMS > Netezza vs. Pinecone vs. Quasardb

System Properties Comparison Netezza vs. Pinecone vs. Quasardb

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPinecone  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsA managed, cloud-native vector databaseDistributed, high-performance timeseries database
Primary database modelRelational DBMSVector DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitewww.ibm.com/­products/­netezzawww.pinecone.ioquasar.ai
Technical documentationdocs.pinecone.io/­docs/­overviewdoc.quasar.ai/­master
DeveloperIBMPinecone Systems, Incquasardb
Initial release200020192009
Current release3.14.1, January 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemsLinux infoincluded in appliancehostedBSD
Linux
OS X
Windows
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesString, Number, Booleanyes infointeger and binary
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 infowith tags
SQL infoSupport of SQLyesnoSQL-like query language
APIs and other access methodsJDBC
ODBC
OLE DB
RESTful HTTP APIHTTP API
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Python.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono
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 infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient mode
User concepts infoAccess controlUsers with fine-grained authorization conceptCryptographically strong user authentication and audit trail

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More resources
Netezza infoAlso called PureData System for Analytics by IBMPineconeQuasardb
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

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1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

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