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

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

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeDocument storeRelational DBMS
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesrockset.comspark.apache.org/­sql
Technical documentationdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftRocksetApache Software Foundation
Initial release201220192014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemshostedhostedLinux
OS X
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesdynamic typingyes
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.nono infoingestion from XML files supportedno
Secondary indexesnoall fields are automatically indexedno
SQL infoSupport of SQLnoRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIHTTP RESTJDBC
ODBC
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceAutomatic shardingyes, 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.yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnono
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.nono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
Microsoft Azure Table StorageRocksetSpark SQL
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