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DBMS > Microsoft Azure Table Storage vs. Netezza vs. Prometheus vs. RDF4J

System Properties Comparison Microsoft Azure Table Storage vs. Netezza vs. Prometheus vs. RDF4J

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonPrometheus  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsData warehouse and analytics appliance part of IBM PureSystemsOpen-source Time Series DBMS and monitoring systemRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelWide column storeRelational DBMSTime Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.ibm.com/­products/­netezzaprometheus.iordf4j.org
Technical documentationprometheus.io/­docsrdf4j.org/­documentation
DeveloperMicrosoftIBMSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2012200020152004
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJava
Server operating systemshostedLinux infoincluded in applianceLinux
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeyesyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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.nono infoImport of XML data possible
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyesnono
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
OLE DB
RESTful HTTP/JSON APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresnoyesnoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationyes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencynone
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACIDnoACID 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.nono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesUsers with fine-grained authorization conceptnono

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More resources
Microsoft Azure Table StorageNetezza infoAlso called PureData System for Analytics by IBMPrometheusRDF4J infoformerly known as Sesame
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