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DBMS > Amazon Aurora vs. Google Cloud Datastore vs. ObjectBox vs. RDF4J

System Properties Comparison Amazon Aurora vs. Google Cloud Datastore vs. ObjectBox vs. RDF4J

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonObjectBox  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformLightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectorsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument storeObject oriented DBMS
Vector DBMS
RDF store
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
#7  Vector DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­datastoregithub.com/­objectbox
objectbox.io
rdf4j.org
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­datastore/­docsdocs.objectbox.iordf4j.org/­documentation
DeveloperAmazonGoogleObjectBox LimitedSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2015200820172004
Current release4.0 (May 2024)
License infoCommercial or Open SourcecommercialcommercialBindings are released under Apache 2.0 infoApache License 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++Java
Server operating systemshostedhostedAndroid
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
Linux
OS X
Unix
Windows
Data schemeyesschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, details hereyes, plus "flex" map-like typesyes
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.yesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)nono
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary native APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
Java
PHP
Python
Server-side scripts infoStored proceduresyesusing Google App Enginenoyes
TriggersyesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosData sync between devices allowing occasional connected databases to work completely offlinenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesno
More information provided by the system vendor
Amazon AuroraGoogle Cloud DatastoreObjectBoxRDF4J infoformerly known as Sesame
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More resources
Amazon AuroraGoogle Cloud DatastoreObjectBoxRDF4J infoformerly known as Sesame
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