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DBMS > Microsoft Azure Table Storage vs. RethinkDB vs. Spark SQL vs. Transbase

System Properties Comparison Microsoft Azure Table Storage vs. RethinkDB vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonRethinkDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsDBMS for the Web with a mechanism to push updated query results to applications in realtime.Spark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelWide column storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.92
Rank#73  Overall
#6  Wide column stores
Score2.84
Rank#106  Overall
#19  Document stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesrethinkdb.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationrethinkdb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperMicrosoftThe Linux Foundation infosince July 2017Apache Software FoundationTransaction Software GmbH
Initial release2012200920141987
Current release2.4.1, August 20203.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0commercial 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 languageC++ScalaC and C++
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infostring, binary, float, bool, date, geometryyesyes
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 indexesnoyesnoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnonoyes
TriggersnoClient-side triggers through changefeedsnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding inforange basedyes, utilizing Spark Core
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 replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingAtomic single-document operationsnoyes
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCC basedyesyes
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 signaturesyes infousers and table-level permissionsnofine grained access rights according to SQL-standard

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More resources
Microsoft Azure Table StorageRethinkDBSpark SQLTransbase
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