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DBMS > Kinetica vs. Microsoft Azure Table Storage vs. OceanBase vs. RDF4J

System Properties Comparison Kinetica vs. Microsoft Azure Table Storage vs. OceanBase vs. RDF4J

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOceanBase  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsA distributed, high available RDBMS compatible with Oracle and MySQLRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSWide column storeRelational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score1.57
Rank#149  Overall
#69  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablesen.oceanbase.comrdf4j.org
Technical documentationdocs.kinetica.comen.oceanbase.com/­docs/­oceanbase-databaserdf4j.org/­documentation
DeveloperKineticaMicrosoftOceanBase infopreviously Alibaba and Ant GroupSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2012201220102004
Current release7.1, August 20214.3.0, April 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoCommercial license availableOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++Java
Server operating systemsLinuxhostedLinuxLinux
OS X
Unix
Windows
Data schemeyesschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnoPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible modeyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning (by hash, key, range, range columns, list, and list columns)none
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standardno

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More resources
KineticaMicrosoft Azure Table StorageOceanBaseRDF4J infoformerly known as Sesame
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