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

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

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKeyDB  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 PlatformAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument storeKey-value 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
Score4.36
Rank#72  Overall
#12  Document stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­datastoregithub.com/­Snapchat/­KeyDB
keydb.dev
rdf4j.org
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­datastore/­docsdocs.keydb.devrdf4j.org/­documentation
DeveloperAmazonGoogleEQ Alpha Technology Ltd.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2015200820192004
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-3Open 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++Java
Server operating systemshostedhostedLinuxLinux
OS X
Unix
Windows
Data schemeyesschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, details herepartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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 indexesyesyesyes infoby using the Redis Search moduleyes
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 protocol infoRESP - REdis Serialization ProtocoJava 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#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Java
PHP
Python
Server-side scripts infoStored proceduresyesusing Google App EngineLuayes
TriggersyesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosMulti-source replication
Source-replica replication
none
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.Eventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsOptimistic locking, atomic execution of commands blocks and scriptsACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes 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.yesnoyes
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)simple password-based access control and ACLno

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More resources
Amazon AuroraGoogle Cloud DatastoreKeyDBRDF4J infoformerly known as Sesame
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