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DBMS > Apache IoTDB vs. Kinetica vs. NSDb vs. PlanetScale vs. TimesTen

System Properties Comparison Apache IoTDB vs. Kinetica vs. NSDb vs. PlanetScale vs. TimesTen

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonPlanetScale  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 CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesScalable, distributed, serverless MySQL database platform built on top of VitessIn-Memory RDBMS compatible to Oracle
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial 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
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websiteiotdb.apache.orgwww.kinetica.comnsdb.ioplanetscale.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.kinetica.comnsdb.io/­Architectureplanetscale.com/­docsdocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software FoundationKineticaPlanetScaleOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20182012201720201998
Current release1.1.0, April 20237.1, August 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++Java, ScalaGo
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
macOS
Docker
Linux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyesyes
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.nononono
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsSQL-like query languageyes infowith proprietary extensionsyes
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
ADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyesuser defined functionsnoyes infoproprietary syntaxPL/SQL
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingShardingnone
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 replicationMulti-source replication
Source-replica replication
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 configurationEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyesyes 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 RAMyesyes
User concepts infoAccess controlyesAccess rights for users and roles on table levelUsers with fine-grained authorization concept infono user groups or rolesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBKineticaNSDbPlanetScaleTimesTen
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