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DBMS > Microsoft Azure Table Storage vs. Oracle NoSQL vs. Spark SQL

System Properties Comparison Microsoft Azure Table Storage vs. Oracle NoSQL vs. Spark SQL

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeDocument store
Key-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.48
Rank#75  Overall
#6  Wide column stores
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.oracle.com/­database/­nosql/­technologies/­nosqlspark.apache.org/­sql
Technical documentationdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftOracleApache Software Foundation
Initial release201220112014
Current release23.3, December 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemshostedLinux
Solaris SPARC/x86
Linux
OS X
Windows
Data schemeschema-freeSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.yes
Typing infopredefined data types such as float or dateyesoptionalyes
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 indexesnoyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIJDBC
ODBC
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
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 serviceShardingyes, 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.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table featurenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingconfigurable infoACID within a storage node (=shard)no
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.noyes infooff heap cacheno
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesAccess rights for users and rolesno

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More resources
Microsoft Azure Table StorageOracle NoSQLSpark SQL
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