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DBMS > Apache Doris vs. Google Cloud Datastore vs. Kinetica vs. RDF4J vs. searchxml

System Properties Comparison Apache Doris vs. Google Cloud Datastore vs. Kinetica vs. RDF4J vs. searchxml

Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonsearchxml  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAutomatically 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.DBMS for structured and unstructured content wrapped with an application server
Primary database modelRelational DBMSDocument storeRelational DBMSRDF storeNative XML DBMS
Search engine
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Websitedoris.apache.org
github.com/­apache/­doris
cloud.google.com/­datastorewww.kinetica.comrdf4j.orgwww.searchxml.net/­category/­products
Technical documentationgithub.com/­apache/­doris/­wikicloud.google.com/­datastore/­docsdocs.kinetica.comrdf4j.org/­documentationwww.searchxml.net/­support/­handouts
DeveloperApache Software Foundation, originally contributed from BaiduGoogleKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.informationpartners gmbh
Initial release20172008201220042015
Current release1.2.2, February 20237.1, August 20211.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++JavaC++
Server operating systemsLinuxhostedLinuxLinux
OS X
Unix
Windows
Windows
Data schemeyesschema-freeyesyes infoRDF Schemasschema-free
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.nononoyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
MySQL client
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
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languagesJava.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineuser defined functionsyesyes infoon the application server
TriggersnoCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSource-replica replicationnoneyes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes 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 integritynoyes 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 usedmultiple readers, single writer
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.nonoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelnoDomain, group and role-based access control at the document level and for application services

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More resources
Apache DorisGoogle Cloud DatastoreKineticaRDF4J infoformerly known as Sesamesearchxml
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