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DBMS > GBase vs. Google Cloud Datastore vs. Kinetica vs. MonetDB vs. RDF4J

System Properties Comparison GBase vs. Google Cloud Datastore vs. Kinetica vs. MonetDB vs. RDF4J

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonMonetDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAn analytical database for business intelligence with large customers in China.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsA relational database management system that stores data in columnsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#190  Overall
#88  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score1.72
Rank#148  Overall
#68  Relational DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Websitewww.gbase.cncloud.google.com/­datastorewww.kinetica.comwww.monetdb.orgrdf4j.org
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comwww.monetdb.org/­Documentationrdf4j.org/­documentation
DeveloperGoogleKineticaMonetDB BVSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201220042004
Current releaseGBase 8a7.1, August 2021Dec2023 (11.49), December 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoMozilla Public License 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++CJava
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeyesyesyes infoRDF Schemas
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsyes infoSQL 2003 with some extensionsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
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++
Java
JavaScript (Node.js)
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsyes, in SQL, C, Ryes
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding via remote tablesnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationnone infoSource-replica replication available in experimental statusnone
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 Consistency or Eventual Consistency depending on configuration
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 TransactionsnoACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
GBaseGoogle Cloud DatastoreKineticaMonetDBRDF4J infoformerly known as Sesame
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