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

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

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSDocument storeRelational DBMSRDF storeTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.gbase.cncloud.google.com/­datastorewww.kinetica.comrdf4j.orgwww.timescale.com
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comrdf4j.org/­documentationdocs.timescale.com
DeveloperGeneral Data Technology Co., Ltd.GoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Timescale
Initial release20042008201220042017
Current releaseGBase 8a, GBase 8s, GBase 8c7.1, August 20212.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonC, C++JavaC
Server operating systemsLinuxhostedLinuxLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesnonoyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLStandard with numerous extensionsSQL-like query language (GQL)SQL-like DML and DDL statementsnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineuser defined functionsyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersyesCallbacks 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 nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardingnoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosSource-replica replicationnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 infoGPU vRAM or System RAMno
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelnofine grained access rights according to SQL-standard

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More resources
GBaseGoogle Cloud DatastoreKineticaRDF4J infoformerly known as SesameTimescaleDB
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