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DBMS > Apache IoTDB vs. Quasardb vs. TimescaleDB vs. VictoriaMetrics vs. Yanza

System Properties Comparison Apache IoTDB vs. Quasardb vs. TimescaleDB vs. VictoriaMetrics vs. Yanza

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonQuasardb  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkDistributed, 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 solutionTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSTime Series DBMSTime Series DBMSTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteiotdb.apache.orgquasar.aiwww.timescale.comvictoriametrics.comyanza.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldoc.quasar.ai/­masterdocs.timescale.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software FoundationquasardbTimescaleVictoriaMetricsYanza
Initial release20182009201720182015
Current release1.1.0, April 20233.14.1, January 20242.15.0, May 2024v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0Open Source infoApache Version 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++CGo
Server operating systemsAll OS with a Java VM (>= 1.8)BSD
Linux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Windows
Data schemeyesschema-freeyesschema-free
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 typesno
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.nonoyesnono
Secondary indexesyesyes infowith tagsyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyes infofull PostgreSQL SQL syntaxnono
APIs and other access methodsJDBC
Native API
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
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.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
any language that supports HTTP calls
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 shellnono
Triggersyesnoyesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoconsistent hashingyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication with selectable replication factorSource-replica replication with hot standby and reads on replicas infoSynchronous replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkwith Hadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoTransient modenono
User concepts infoAccess controlyesCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standardno

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More resources
Apache IoTDBQuasardbTimescaleDBVictoriaMetricsYanza
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