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DBMS > Google Cloud Datastore vs. MarkLogic vs. RDF4J vs. Yaacomo

System Properties Comparison Google Cloud Datastore vs. MarkLogic vs. RDF4J vs. Yaacomo

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMarkLogic  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOperational and transactional Enterprise NoSQL databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
RDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­datastorewww.marklogic.comrdf4j.orgyaacomo.com
Technical documentationcloud.google.com/­datastore/­docsdocs.marklogic.comrdf4j.org/­documentation
DeveloperGoogleMarkLogic Corp.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.Q2WEB GmbH
Initial release2008200120042009
Current release11.0, December 2022
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Unix
Windows
Android
Linux
Windows
Data schemeschema-freeschema-free infoSchema can be enforcedyes infoRDF Schemasyes
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.noyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infoSQL92noyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyes infovia XQuery or JavaScriptyes
TriggersCallbacks using the Google Apps Engineyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosyesnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
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 pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infocan act as a resource manager in an XA/JTA transactionACID 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.noyes, with Range Indexesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreMarkLogicRDF4J infoformerly known as SesameYaacomo
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