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DBMS > Microsoft Azure Table Storage vs. Realm vs. Spark SQL vs. TigerGraph

System Properties Comparison Microsoft Azure Table Storage vs. Realm vs. Spark SQL vs. TigerGraph

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelWide column storeDocument storeRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.48
Rank#75  Overall
#6  Wide column stores
Score7.60
Rank#52  Overall
#9  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesrealm.iospark.apache.org/­sqlwww.tigergraph.com
Technical documentationrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperMicrosoftRealm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release2012201420142017
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++
Server operating systemshostedAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesnoyesno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnono inforuns within the applications so server-side scripts are unnecessarynoyes
Triggersnoyes infoChange Listenersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenoneyes, 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.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyes infoIn-Memory realmnono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesyesnoRole-based access control

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More resources
Microsoft Azure Table StorageRealmSpark SQLTigerGraph
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