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DBMS > Microsoft Azure Table Storage vs. Quasardb vs. Spark SQL vs. Tkrzw

System Properties Comparison Microsoft Azure Table Storage vs. Quasardb vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelWide column storeTime Series DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesquasar.aispark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationdoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftquasardbApache Software FoundationMikio Hirabayashi
Initial release2012200920142020
Current release3.14.1, January 20243.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemshostedBSD
Linux
OS X
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes infointeger and binaryyesno
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 indexesnoyes infowith tagsno
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIHTTP APIJDBC
ODBC
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashingyes, utilizing Spark Corenone
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 replication with selectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modenoyes infousing specific database classes
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesCryptographically strong user authentication and audit trailnono

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Microsoft Azure Table StorageQuasardbSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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