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DBMS > Apache IoTDB vs. Google Cloud Firestore vs. IRONdb vs. RDF4J vs. TerarkDB

System Properties Comparison Apache IoTDB vs. Google Cloud Firestore vs. IRONdb vs. RDF4J vs. TerarkDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTerarkDB  Xexclude from comparison
IRONdb 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 FlinkCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelTime Series DBMSDocument storeTime Series DBMSRDF storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.08
Rank#367  Overall
#56  Key-value stores
Websiteiotdb.apache.orgfirebase.google.com/­products/­firestorewww.circonus.com/solutions/time-series-database/rdf4j.orggithub.com/­bytedance/­terarkdb
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­firestoredocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software FoundationGoogleCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.ByteDance, originally Terark
Initial release20182017201720042016
Current release1.1.0, April 2023V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++JavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedLinuxLinux
OS X
Unix
Windows
Data schemeyesschema-freeschema-freeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyesno
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 indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsJDBC
Native API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
C++ API
Java API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
C++
Java
Server-side scripts infoStored proceduresyesyes, Firebase Rules & Cloud Functionsyes, in Luayesno
Triggersyesyes, with Cloud Functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingAutomatic, metric affinity per nodenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkUsing Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.nonono

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More resources
Apache IoTDBGoogle Cloud FirestoreIRONdbRDF4J infoformerly known as SesameTerarkDB
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