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

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

Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAn embeddable, in-process, column-oriented SQL OLAP RDBMSWidely 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.
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.57
Rank#74  Overall
#40  Relational DBMS
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
Websiteduckdb.orgwww.gbase.cncloud.google.com/­datastorewww.kinetica.comrdf4j.org
Technical documentationduckdb.org/­docscloud.google.com/­datastore/­docsdocs.kinetica.comrdf4j.org/­documentation
DeveloperGeneral Data Technology Co., Ltd.GoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20182004200820122004
Current release0.10, February 2024GBase 8a, GBase 8s, GBase 8c7.1, August 2021
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, Java, PythonC, C++Java
Server operating systemsserver-lessLinuxhostedLinuxLinux
OS X
Unix
Windows
Data schemeyesyesschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes, 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.noyesnono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesStandard with numerous extensionsSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
ADO.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
Supported programming languagesC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functionsusing Google App Engineuser defined functionsyes
TriggersnoyesCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlnoyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelno

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More resources
DuckDBGBaseGoogle Cloud DatastoreKineticaRDF4J infoformerly known as Sesame
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