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DBMS > Kinetica vs. LevelDB vs. Microsoft Azure Table Storage vs. Netezza vs. RDF4J

System Properties Comparison Kinetica vs. LevelDB vs. Microsoft Azure Table Storage vs. Netezza vs. RDF4J

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA Wide Column Store for rapid development using massive semi-structured datasetsData warehouse and analytics appliance part of IBM PureSystemsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSKey-value storeWide column storeRelational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitewww.kinetica.comgithub.com/­google/­leveldbazure.microsoft.com/­en-us/­services/­storage/­tableswww.ibm.com/­products/­netezzardf4j.org
Technical documentationdocs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdrdf4j.org/­documentation
DeveloperKineticaGoogleMicrosoftIBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20122011201220002004
Current release7.1, August 20211.23, February 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSDcommercialcommercialOpen 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++C++Java
Server operating systemsLinuxIllumos
Linux
OS X
Windows
hostedLinux infoincluded in applianceLinux
OS X
Unix
Windows
Data schemeyesschema-freeschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonono
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
OLE DB
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
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnonoyesyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyesyes 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 levelnoAccess rights based on private key authentication or shared access signaturesUsers with fine-grained authorization conceptno

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More resources
KineticaLevelDBMicrosoft Azure Table StorageNetezza infoAlso called PureData System for Analytics by IBMRDF4J infoformerly known as Sesame
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