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DBMS > Apache IoTDB vs. Quasardb vs. TimescaleDB vs. TimesTen vs. Tkrzw

System Properties Comparison Apache IoTDB vs. Quasardb vs. TimescaleDB vs. TimesTen vs. Tkrzw

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonQuasardb  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTimesTen  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
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 PostgreSQLIn-Memory RDBMS compatible to OracleA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelTime Series DBMSTime Series DBMSTime Series DBMSRelational DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteiotdb.apache.orgquasar.aiwww.timescale.comwww.oracle.com/­database/­technologies/­related/­timesten.htmldbmx.net/­tkrzw
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldoc.quasar.ai/­masterdocs.timescale.comdocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software FoundationquasardbTimescaleOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005Mikio Hirabayashi
Initial release20182009201719982020
Current release1.1.0, April 20233.14.1, January 20242.13.0, November 202311 Release 2 (11.2.2.8.0)0.9.3, August 2020
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 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++CC++
Server operating systemsAll OS with a Java VM (>= 1.8)BSD
Linux
OS X
Windows
Linux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
macOS
Data schemeyesschema-freeyesyesschema-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 typesyesno
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 tagsyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyes infofull PostgreSQL SQL syntaxyesno
APIs and other access methodsJDBC
Native API
HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
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
C
C++
Java
PL/SQL
C++
Java
Python
Ruby
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 shellPL/SQLno
Triggersyesnoyesnono
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) attributesnonenone
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 infoMulti-source replication
Source-replica replication
none
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoTransient modenoyesyes infousing specific database classes
User concepts infoAccess controlyesCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
Apache IoTDBQuasardbTimescaleDBTimesTenTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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