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DBMS > GBase vs. Google Cloud Datastore vs. IBM Db2 Event Store vs. Kinetica vs. RDF4J

System Properties Comparison GBase vs. Google Cloud Datastore vs. IBM Db2 Event Store vs. Kinetica vs. RDF4J

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonKinetica  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 PlatformDistributed Event Store optimized for Internet of Things use casesFully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument storeEvent Store
Time Series DBMS
Relational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.05
Rank#193  Overall
#90  Relational DBMS
Score4.87
Rank#78  Overall
#12  Document stores
Score0.25
Rank#320  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score0.72
Rank#234  Overall
#9  RDF stores
Websitewww.gbase.cncloud.google.com/­datastorewww.ibm.com/­products/­db2-event-storewww.kinetica.comrdf4j.org
Technical documentationcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-storedocs.kinetica.comrdf4j.org/­documentation
DeveloperGoogleIBMKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720122004
Current releaseGBase 8a2.07.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availablecommercialOpen 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 and C++C, C++Java
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionLinuxLinux
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
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++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyesuser defined functionsyes
TriggersCallbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosActive-active shard replicationSource-replica replicationnone
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.Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
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 TransactionsnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes 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.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users and roles on table levelno

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More resources
GBaseGoogle Cloud DatastoreIBM Db2 Event StoreKineticaRDF4J infoformerly known as Sesame
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