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DBMS > Microsoft Azure Table Storage vs. Spark SQL vs. SWC-DB vs. Transbase

System Properties Comparison Microsoft Azure Table Storage vs. Spark SQL vs. SWC-DB vs. Transbase

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMSA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelWide column storeRelational DBMSWide column storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.48
Rank#75  Overall
#6  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
www.transaction.de/­en/­products/­transbase.html
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperMicrosoftApache Software FoundationAlex KashirinTransaction Software GmbH
Initial release2012201420201987
Current release3.5.0 ( 2.13), September 20230.5, April 2021Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPL V3commercial infofree development license
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C and C++
Server operating systemshostedLinux
OS X
Windows
LinuxFreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesnonoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
Thrift
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C++C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnononoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnoyes
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.nononono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesnofine grained access rights according to SQL-standard

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More resources
Microsoft Azure Table StorageSpark SQLSWC-DB infoSuper Wide Column DatabaseTransbase
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