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DBMS > Netezza vs. Quasardb vs. TimescaleDB vs. VictoriaMetrics

System Properties Comparison Netezza vs. Quasardb vs. TimescaleDB vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQuasardb  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsDistributed, high-performance timeseries databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.ibm.com/­products/­netezzaquasar.aiwww.timescale.comvictoriametrics.com
Technical documentationdoc.quasar.ai/­masterdocs.timescale.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperIBMquasardbTimescaleVictoriaMetrics
Initial release2000200920172018
Current release3.14.1, January 20242.13.0, November 2023v1.91, May 2023
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CGo
Server operating systemsLinux infoincluded in applianceBSD
Linux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infointeger and binarynumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyesno
Secondary indexesyesyes infowith tagsyes
SQL infoSupport of SQLyesSQL-like query languageyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with selectable replication factorSource-replica replication with hot standby and reads on replicas infoSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyeswith Hadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoTransient modenono
User concepts infoAccess controlUsers with fine-grained authorization conceptCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard

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More resources
Netezza infoAlso called PureData System for Analytics by IBMQuasardbTimescaleDBVictoriaMetrics
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

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

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

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

IBM Brings Back a Netezza, Attacks Yellowbrick
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TimescaleDB Is a Vector Database Now, Too
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Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

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16 May 2023, Embedded Computing Design

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OpenTelemetry Is Too Complicated, VictoriaMetrics Says
1 April 2024, Datanami

KubeCon24: VictoriaMetrics' Simpler Alternative to Prometheus
20 March 2024, The New Stack

How VictoriaMetrics' open source approach led to mass industry adoption
3 May 2024, Tech.eu

VictoriaMetrics Machine Learning takes monitoring to the next level
19 March 2024, Business Wire

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