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DBMS > Google Cloud Datastore vs. MarkLogic vs. RDF4J

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

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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 comparison
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.
Primary database modelDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.84
Rank#76  Overall
#11  Document stores
Score9.19
Rank#51  Overall
#8  Document stores
#1  Native XML DBMS
#1  RDF stores
#4  Search engines
Score0.68
Rank#211  Overall
#9  RDF stores
Websitecloud.google.com/­datastorewww.marklogic.comrdf4j.org
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.
Initial release200820012004
Current release9.0, 2017
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnono
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
Data schemeschema-freeschema-free infoSchema can be enforcedyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes, details hereyesyes
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
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infoSQL92no
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
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 Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
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
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsno
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 used
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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, with Range Indexes
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 levelsno
More information provided by the system vendor
Google Cloud DatastoreMarkLogicRDF4J infoformerly known as Sesame
Specific characteristicsThe MarkLogic Multi-Model Database provides the simplest way to integrate data from...
» more
Competitive advantagesThe main benefit of MarkLogic is simplicity. By making things simpler, MarkLogic...
» more
Typical application scenariosMarkLogic’s main use case is the Operational Data Hub . A Data Hub is useful for...
» more
Key customersMarkLogic has proven results managing mission-critical data with over 1,000 global...
» more
Market metricsMarkLogic is well known within the Fortune 1000, with a strong presence in financial...
» more
Licensing and pricing modelsMarkLogic provides a variety of licenses and cloud services: MarkLogic Data Hub Service...
» more

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More resources
Google Cloud DatastoreMarkLogicRDF4J infoformerly known as Sesame
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