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DBMS > Apache IoTDB vs. Kinetica vs. Microsoft Azure Table Storage vs. NSDb vs. TimesTen

System Properties Comparison Apache IoTDB vs. Kinetica vs. Microsoft Azure Table Storage vs. NSDb vs. TimesTen

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonNSDb  Xexclude from comparisonTimesTen  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 FlinkFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesIn-Memory RDBMS compatible to Oracle
Primary database modelTime Series DBMSRelational DBMSWide column storeTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websiteiotdb.apache.orgwww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablesnsdb.iowww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.kinetica.comnsdb.io/­Architecturedocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software FoundationKineticaMicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20182012201220171998
Current release1.1.0, April 20237.1, August 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++Java, Scala
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxhostedLinux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes: int, bigint, decimal, stringyes
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.nonononono
Secondary indexesyesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoSQL-like query languageyes
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIgRPC
HTTP REST
WebSocket
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyesuser defined functionsnonoPL/SQL
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoImplicit feature of the cloud serviceShardingnone
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 replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlyesAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBKineticaMicrosoft Azure Table StorageNSDbTimesTen
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