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DBMS > Apache IoTDB vs. Kinetica vs. RavenDB vs. SWC-DB vs. Yanza

System Properties Comparison Apache IoTDB vs. Kinetica vs. RavenDB vs. SWC-DB vs. Yanza

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonKinetica  Xexclude from comparisonRavenDB  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 FlinkFully vectorized database across both GPUs and CPUsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA high performance, scalable Wide Column DBMSTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSRelational DBMSDocument storeWide column storeTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Graph DBMS
Spatial DBMS
Time Series 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
Score2.92
Rank#101  Overall
#18  Document stores
Score0.01
Rank#376  Overall
#13  Wide column stores
Websiteiotdb.apache.orgwww.kinetica.comravendb.netgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
yanza.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.kinetica.comravendb.net/­docs
DeveloperApache Software FoundationKineticaHibernating RhinosAlex KashirinYanza
Initial release20182012201020202015
Current release1.1.0, April 20237.1, August 20215.4, July 20220.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoGPL V3commercial 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, C++C#C++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
macOS
Raspberry Pi
Windows
LinuxWindows
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsSQL-like query language (RQL)SQL-like query languageno
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Proprietary protocol
Thrift
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++any language that supports HTTP calls
Server-side scripts infoStored proceduresyesuser defined functionsyesnono
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnoyes infoTimer and event based
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 replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, Cluster-wide transaction availableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlyesAccess rights for users and roles on table levelAuthorization levels configured per client per databaseno

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More resources
Apache IoTDBKineticaRavenDBSWC-DB infoSuper Wide Column DatabaseYanza
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