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DBMS > Google Cloud Firestore vs. Hive vs. Kinetica vs. RDF4J vs. Sadas Engine

System Properties Comparison Google Cloud Firestore vs. Hive vs. Kinetica vs. RDF4J vs. Sadas Engine

Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHive  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSadas Engine  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.data warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument storeRelational DBMSRelational DBMSRDF storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitefirebase.google.com/­products/­firestorehive.apache.orgwww.kinetica.comrdf4j.orgwww.sadasengine.com
Technical documentationfirebase.google.com/­docs/­firestorecwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.comrdf4j.org/­documentationwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SADAS s.r.l.
Initial release20172012201220042006
Current release3.1.3, April 20227.1, August 20218.0
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial infofree trial version available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++JavaC++
Server operating systemshostedAll OS with a Java VMLinuxLinux
OS X
Unix
Windows
AIX
Linux
Windows
Data schemeschema-freeyesyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statementsnoyes
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes infouser defined functions and integration of map-reduceuser defined functionsyesno
Triggersyes, with Cloud Functionsnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factorSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACID infoIsolation support depends on the API used
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.yes infoGPU vRAM or System RAMyes infomanaged by 'Learn by Usage'
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, groups and rolesAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud FirestoreHiveKineticaRDF4J infoformerly known as SesameSadas Engine
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