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DBMS > Apache IoTDB vs. Kinetica vs. Riak KV vs. SpaceTime vs. WakandaDB

System Properties Comparison Apache IoTDB vs. Kinetica vs. Riak KV vs. SpaceTime vs. WakandaDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonKinetica  Xexclude from comparisonRiak KV  Xexclude from comparisonSpaceTime  Xexclude from comparisonWakandaDB  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 CPUsDistributed, fault tolerant key-value storeSpaceTime is a spatio-temporal DBMS with a focus on performance.WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelTime Series DBMSRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesSpatial DBMSObject oriented DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websiteiotdb.apache.orgwww.kinetica.comwww.mireo.com/­spacetimewakanda.github.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.kinetica.comwww.tiot.jp/­riak-docs/­riak/­kv/­latestwakanda.github.io/­doc
DeveloperApache Software FoundationKineticaOpenSource, formerly Basho TechnologiesMireoWakanda SAS
Initial release20182012200920202012
Current release1.1.0, April 20237.1, August 20213.2.0, December 20222.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2, commercial enterprise editioncommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ErlangC++C++, JavaScript
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
LinuxLinux
OS X
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 indexesyesyesrestrictedno
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoA subset of ANSI SQL is implementedno
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
RESTful HTTP APIRESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
JavaScript (Node.js)
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
C++
Python
JavaScript
Server-side scripts infoStored proceduresyesuser defined functionsErlangnoyes
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infopre-commit hooks and post-commit hooksnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infono "single point of failure"Fixed-grid hypercubesnone
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 replicationselectable replication factorReal-time block device replication (DRBD)none
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 configurationEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
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 RAMnono
User concepts infoAccess controlyesAccess rights for users and roles on table levelyes, using Riak Securityyesyes

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More resources
Apache IoTDBKineticaRiak KVSpaceTimeWakandaDB
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