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DBMS > Apache IoTDB vs. Firebase Realtime Database vs. Kinetica vs. Kingbase vs. Riak TS

System Properties Comparison Apache IoTDB vs. Firebase Realtime Database vs. Kinetica vs. Kingbase vs. Riak TS

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonKinetica  Xexclude from comparisonKingbase  Xexclude from comparisonRiak TS  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 FlinkCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Fully vectorized database across both GPUs and CPUsAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelTime Series DBMSDocument storeRelational DBMSRelational DBMSTime Series 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
Score14.29
Rank#39  Overall
#6  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.45
Rank#262  Overall
#123  Relational DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websiteiotdb.apache.orgfirebase.google.com/­products/­realtime-databasewww.kinetica.comwww.kingbase.com.cn
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­databasedocs.kinetica.comwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperApache Software FoundationGoogle infoacquired by Google 2014KineticaBeiJing KINGBASE Information technologies inc.Open Source, formerly Basho Technologies
Initial release20182012201219992015
Current release1.1.0, April 20237.1, August 2021V8.0, August 20213.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C and JavaErlang
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinuxLinux
Windows
Linux
OS X
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononoyesno
Secondary indexesyesyesyesyesrestricted
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsStandard with numerous extensionsyes, limited
APIs and other access methodsJDBC
Native API
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
HTTP API
Native Erlang Interface
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
JavaScript
Objective-C
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
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
Server-side scripts infoStored proceduresyeslimited functionality with using 'rules'user defined functionsuser defined functionsErlang
TriggersyesCallbacks are triggered when data changesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding
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 replicationyesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesyesno infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDno
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 RAM
User concepts infoAccess controlyesyes, based on authentication and database rulesAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
Apache IoTDBFirebase Realtime DatabaseKineticaKingbaseRiak TS
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