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

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

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSKey-value storeDocument storeRDF store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteaws.amazon.com/­rds/­auroraetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorerdf4j.org
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsrdf4j.org/­documentation
DeveloperAmazonGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release201520082004
Current release3.4, August 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Unix
Windows
Data schemeyesschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesnoyes, details hereyes
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 indexesyesnoyesyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)no
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java 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
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresyesnousing Google App Engineyes
Triggersyesyes, watching key changesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID 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-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Amazon AuroraetcdGoogle Cloud DatastoreRDF4J infoformerly known as Sesame
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