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DBMS > Apache IoTDB vs. Firebase Realtime Database vs. GridGain vs. Riak TS

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGridGain  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.GridGain is an in-memory computing platform, built on Apache IgniteRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelTime Series DBMSDocument storeKey-value store
Relational 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
Score14.29
Rank#39  Overall
#6  Document stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websiteiotdb.apache.orgfirebase.google.com/­products/­realtime-databasewww.gridgain.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­databasewww.gridgain.com/­docs/­index.htmlwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperApache Software FoundationGoogle infoacquired by Google 2014GridGain Systems, Inc.Open Source, formerly Basho Technologies
Initial release2018201220072015
Current release1.1.0, April 2023GridGain 8.5.13.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetErlang
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinux
OS X
Solaris
Windows
Linux
OS X
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nonoyesno
Secondary indexesyesyesyesrestricted
SQL infoSupport of SQLSQL-like query languagenoANSI-99 for query and DML statements, subset of DDLyes, limited
APIs and other access methodsJDBC
Native API
Android
iOS
JavaScript API
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Native Erlang Interface
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
JavaScript
Objective-C
C#
C++
Java
PHP
Python
Ruby
Scala
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'yes (compute grid and cache interceptors can be used instead)Erlang
TriggersyesCallbacks are triggered when data changesyes (cache interceptors and events)yes 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)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes (replicated cache)selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes (compute grid and hadoop accelerator)yes
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlyesyes, based on authentication and database rulesSecurity Hooks for custom implementationsno

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More resources
Apache IoTDBFirebase Realtime DatabaseGridGainRiak TS
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