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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDatabase 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.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument storeRelational DBMSRDF storeTime Series DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­databaserdf4j.orgwww.timescale.com
Technical documentationcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlrdf4j.org/­documentationdocs.timescale.com
DeveloperGoogleMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Timescale
Initial release2008201020042017
Current releaseV122.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC
Server operating systemshostedhostedLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyes, details hereyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yesnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresusing Google App EngineTransact SQLyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersCallbacks using the Google Apps Engineyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes, with always 3 replicas availablenoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes 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.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureRDF4J infoformerly known as SesameTimescaleDB
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