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DBMS > Google Cloud Firestore vs. Kinetica vs. RDF4J vs. Riak TS

System Properties Comparison Google Cloud Firestore vs. Kinetica vs. RDF4J vs. Riak TS

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRiak TS  Xexclude from comparison
DescriptionCloud 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.Fully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelDocument storeRelational DBMSRDF storeTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.96
Rank#48  Overall
#8  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Score0.25
Rank#308  Overall
#26  Time Series DBMS
Websitefirebase.google.com/­products/­firestorewww.kinetica.comrdf4j.org
Technical documentationfirebase.google.com/­docs/­firestoredocs.kinetica.comrdf4j.org/­documentationwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperGoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Open Source, formerly Basho Technologies
Initial release2017201220042015
Current release7.1, August 20213.0.0, September 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaErlang
Server operating systemshostedLinuxLinux
OS X
Unix
Windows
Linux
OS X
Data schemeschema-freeyesyes infoRDF Schemasschema-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.nonono
Secondary indexesyesyesyesrestricted
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyes, limited
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
HTTP API
Native Erlang Interface
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
JavaScript (Node.js)
Python
Java
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 proceduresyes, Firebase Rules & Cloud Functionsuser defined functionsyesErlang
Triggersyes, with Cloud Functionsyes 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 nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationnoneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflownonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynoyesno infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.yes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users and roles on table levelnono

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More resources
Google Cloud FirestoreKineticaRDF4J infoformerly known as SesameRiak TS
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