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DBMS > Microsoft Azure Table Storage vs. SiteWhere vs. Spark SQL vs. Warp 10

System Properties Comparison Microsoft Azure Table Storage vs. SiteWhere vs. Spark SQL vs. Warp 10

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelWide column storeTime Series DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­sitewhere/­sitewherespark.apache.org/­sqlwww.warp10.io
Technical documentationsitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperMicrosoftSiteWhereApache Software FoundationSenX
Initial release2012201020142015
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaJava
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freepredefined schemeyesschema-free
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.nononono
Secondary indexesnononono
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIHTTP RESTJDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoWarpScript
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infobased on HBaseyes, utilizing Spark CoreSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBasenoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesUsers with fine-grained authorization conceptnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Microsoft Azure Table StorageSiteWhereSpark SQLWarp 10
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