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DBMS > Google Cloud Datastore vs. Microsoft Azure Table Storage vs. RDF4J vs. SAP HANA vs. UniData,UniVerse

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Table Storage vs. RDF4J vs. SAP HANA vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSAP HANA  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Wide Column Store for rapid development using massive semi-structured datasetsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.In-memory, column based data store. Available as appliance or cloud serviceMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelDocument storeWide column storeRDF storeRelational DBMSMultivalue DBMS
Secondary database modelsDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.87
Rank#78  Overall
#12  Document stores
Score5.35
Rank#71  Overall
#6  Wide column stores
Score0.72
Rank#234  Overall
#9  RDF stores
Score45.49
Rank#22  Overall
#16  Relational DBMS
Score3.93
Rank#89  Overall
#2  Multivalue DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tablesrdf4j.orgwww.sap.com/­products/­hana.htmlwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationcloud.google.com/­datastore/­docsrdf4j.org/­documentationhelp.sap.com/­hanadocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperGoogleMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SAPRocket Software
Initial release20082012200420101985
Current release2.0 SPS07 (April 4, 2023), April 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono infoalso available as a cloud based serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC
Server operating systemshostedhostedLinux
OS X
Unix
Windows
Appliance or cloud-serviceAIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyesoptional
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.nonono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoyesyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresusing Google App EnginenoyesSQLScript, Ryes
TriggersCallbacks using the Google Apps Enginenoyesyesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneyesnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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 pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingACID infoIsolation support depends on the API usedACIDACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesnoyesAccess rights according to SQL-standard and operating system based

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Google Cloud DatastoreMicrosoft Azure Table StorageRDF4J infoformerly known as SesameSAP HANAUniData,UniVerse
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