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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMarkLogic  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically 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 modelRelational DBMSDocument 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
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score4.15
Rank#70  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#8  Search engines
Score0.72
Rank#222  Overall
#9  RDF stores
Websitewww.datomic.comcloud.google.com/­datastorewww.progress.com/­marklogicrdf4j.org
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docswww.progress.com/­marklogic/­documentationrdf4j.org/­documentation
DeveloperCognitectGoogleMarkLogic Corp.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2012200820012004
Current release1.0.7180, July 202411.0, December 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercial inforestricted free version is availableOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++Java
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesschema-freeschema-free infoSchema can be enforcedyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, 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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yes infoSQL92no
APIs and other access methodsRESTful HTTP APIgRPC (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 languagesClojure
Java
.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 proceduresyes infoTransaction Functionsusing Google App Engineyes infovia XQuery or JavaScriptyes
TriggersBy using transaction functionsCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes 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 ConsistencyImmediate 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 integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID 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 datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes 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.yes inforecommended only for testing and developmentnoyes, with Range Indexes
User concepts infoAccess controlnoAccess 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

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More resources
DatomicGoogle Cloud DatastoreMarkLogicRDF4J infoformerly known as Sesame
Conferences, events and webinars

Progress MarkLogic World
Washington DC, 23-25 September 2024

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