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

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

Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  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 processingOpen source search engine for searching in data from different sources, e.g. relational databasesTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelWide column storeTime Series DBMSRelational DBMSSearch engineTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­sitewhere/­sitewherespark.apache.org/­sqlsphinxsearch.comwww.warp10.io
Technical documentationsitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docswww.warp10.io/­content/­02_Getting_started
DeveloperMicrosoftSiteWhereApache Software FoundationSphinx Technologies Inc.SenX
Initial release20122010201420012015
Current release3.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++Java
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freepredefined schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesnononoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)no
APIs and other access methodsRESTful HTTP APIHTTP RESTJDBC
ODBC
Proprietary protocolHTTP API
Jupyter
WebSocket
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnononoyes infoWarpScript
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infobased on HBaseyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding 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 HBasenonenoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
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 conceptnonoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Microsoft Azure Table StorageSiteWhereSpark SQLSphinxWarp 10
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