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DBMS > Google Cloud Datastore vs. Hazelcast vs. Microsoft Azure SQL Database vs. RDF4J

System Properties Comparison Google Cloud Datastore vs. Hazelcast vs. Microsoft Azure SQL Database vs. RDF4J

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridDatabase as a Service offering with high compatibility to Microsoft SQL ServerRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeKey-value storeRelational DBMSRDF store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­datastorehazelcast.comazure.microsoft.com/­en-us/­products/­azure-sql/­databaserdf4j.org
Technical documentationcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlrdf4j.org/­documentation
DeveloperGoogleHazelcastMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008200820102004
Current release5.3.6, November 2023V12
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemshostedAll OS with a Java VMhostedLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.noyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languageyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyes infoEvent Listeners, Executor ServicesTransact SQLyes
TriggersCallbacks using the Google Apps Engineyes infoEventsyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoReplicated Mapyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedACIDACID 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.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standardno

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More resources
Google Cloud DatastoreHazelcastMicrosoft Azure SQL Database infoformerly SQL AzureRDF4J infoformerly known as Sesame
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