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DBMS > GBase vs. Google Cloud Datastore vs. Kinetica vs. Machbase Neo vs. RDF4J

System Properties Comparison GBase vs. Google Cloud Datastore vs. Kinetica vs. Machbase Neo vs. RDF4J

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonRDF4J infoformerly known as Sesame  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 CPUsTimeSeries DBMS for AIoT and BigDataRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument storeRelational DBMSTime Series DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series 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
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.gbase.cncloud.google.com/­datastorewww.kinetica.commachbase.comrdf4j.org
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.commachbase.com/­dbmsrdf4j.org/­documentation
DeveloperGeneral Data Technology Co., Ltd.GoogleKineticaMachbaseSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20042008201220132004
Current releaseGBase 8a, GBase 8s, GBase 8c7.1, August 2021V8.0, August 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infofree test version availableOpen Source infoEclipse Distribution License (EDL), v1.0.
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++CJava
Server operating systemsLinuxhostedLinuxLinux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeyesschema-freeyesyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, 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.yesnonono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLStandard with numerous extensionsSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like query languageno
APIs and other access methodsADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineuser defined functionsnoyes
TriggersyesCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosSource-replica replicationselectable replication factornone
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 configuration
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes 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 RAMyes infovolatile and lookup table
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 levelsimple password-based access controlno

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More resources
GBaseGoogle Cloud DatastoreKineticaMachbase Neo infoFormer name was InfinifluxRDF4J infoformerly known as Sesame
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