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DBMS > Google Cloud Datastore vs. Kinetica vs. RDF4J vs. Sequoiadb vs. WakandaDB

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. RDF4J vs. Sequoiadb vs. WakandaDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSequoiadb  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionAutomatically 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.NewSQL database with distributed OLTP and SQLWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeRelational DBMSRDF storeDocument store
Relational DBMS
Object oriented DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitecloud.google.com/­datastorewww.kinetica.comrdf4j.orgwww.sequoiadb.comwakanda.github.io
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comrdf4j.org/­documentationwww.sequoiadb.com/­en/­index.php?m=Files&a=indexwakanda.github.io/­doc
DeveloperGoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Sequoiadb Ltd.Wakanda SAS
Initial release20082012200420132012
Current release7.1, August 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoServer: AGPL; Client: Apache V2Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++JavaC++C++, JavaScript
Server operating systemshostedLinuxLinux
OS X
Unix
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeyesyes infoRDF Schemasschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes infooid, date, timestamp, binary, regexyes
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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsnoSQL-like query languageno
APIs and other access methodsgRPC (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
proprietary protocol using JSONRESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
.Net
C++
Java
PHP
Python
JavaScript
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsyesJavaScriptyes
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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 configurationEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API usedDocument is locked during a transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnono
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 levelnosimple password-based access controlyes

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More resources
Google Cloud DatastoreKineticaRDF4J infoformerly known as SesameSequoiadbWakandaDB
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