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DBMS > Netezza vs. QuestDB vs. Sphinx vs. SQream DB vs. VictoriaMetrics

System Properties Comparison Netezza vs. QuestDB vs. Sphinx vs. SQream DB vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparisonSQream DB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databasesa GPU-based, columnar RDBMS for big data analytics workloadsA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSTime Series DBMSSearch engineRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitewww.ibm.com/­products/­netezzaquestdb.iosphinxsearch.comsqream.comvictoriametrics.com
Technical documentationquestdb.io/­docssphinxsearch.com/­docsdocs.sqream.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperIBMQuestDB Technology IncSphinx Technologies Inc.SQream TechnologiesVictoriaMetrics
Initial release20002014200120172018
Current release3.5.1, February 20232022.1.6, December 2022v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava (Zero-GC), C++, RustC++C++, CUDA, Haskell, Java, ScalaGo
Server operating systemsLinux infoincluded in applianceLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
LinuxFreeBSD
Linux
macOS
OpenBSD
Data schemeyesyes infoschema-free via InfluxDB Line Protocolyesyes
Typing infopredefined data types such as float or dateyesyesnoyes, ANSI Standard SQL 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.nono
Secondary indexesyesnoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLyesSQL with time-series extensionsSQL-like query language (SphinxQL)yesno
APIs and other access methodsJDBC
ODBC
OLE DB
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol.Net
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnonouser defined functions in Pythonno
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with eventual consistencynonenoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID for single-table writesnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infothrough memory mapped filesno
User concepts infoAccess controlUsers with fine-grained authorization conceptno
More information provided by the system vendor
Netezza infoAlso called PureData System for Analytics by IBMQuestDBSphinxSQream DBVictoriaMetrics
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Netezza infoAlso called PureData System for Analytics by IBMQuestDBSphinxSQream DBVictoriaMetrics
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