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DBMS > Apache IoTDB vs. Tkrzw

System Properties Comparison Apache IoTDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameApache IoTDB  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 FlinkA 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 DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score0.09
Rank#354  Overall
#51  Key-value stores
Websiteiotdb.apache.orgdbmx.net/­tkrzw
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.html
DeveloperApache Software FoundationMikio Hirabayashi
Initial release20182020
Current release1.1.0, April 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesno
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 indexesyes
SQL infoSupport of SQLSQL-like query languageno
APIs and other access methodsJDBC
Native API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)none
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing specific database classes
User concepts infoAccess controlyesno

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Apache IoTDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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