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DBMS > Microsoft Azure Table Storage vs. Spark SQL vs. Yaacomo

System Properties Comparison Microsoft Azure Table Storage vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelWide column storeRelational DBMSRelational 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
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sqlyaacomo.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftApache Software FoundationQ2WEB GmbH
Initial release201220142009
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemshostedLinux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freeyesyes
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.nonono
Secondary indexesnonoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBC
ODBC
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Corehorizontal partitioning
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 methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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 SQLYaacomo
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