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DBMS > DataFS vs. Microsoft Azure Table Storage vs. OrientDB vs. Spark SQL

System Properties Comparison DataFS vs. Microsoft Azure Table Storage vs. OrientDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOrientDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A Wide Column Store for rapid development using massive semi-structured datasetsMulti-model DBMS (Document, Graph, Key/Value)Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSWide column storeDocument store
Graph DBMS
Key-value store
Relational DBMS
Secondary database modelsGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#360  Overall
#18  Object oriented DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score3.25
Rank#89  Overall
#16  Document stores
#6  Graph DBMS
#13  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitenewdatabase.comazure.microsoft.com/­en-us/­services/­storage/­tablesorientdb.orgspark.apache.org/­sql
Technical documentationdev.mobiland.com/­Overview.xspwww.orientdb.com/­docs/­last/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMobiland AGMicrosoftOrientDB LTD; CallidusCloud; SAPApache Software Foundation
Initial release2018201220102014
Current release1.1.263, October 20223.2.29, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScala
Server operating systemsWindowshostedAll OS with a Java JDK (>= JDK 6)Linux
OS X
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")yes
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 indexesnonoyesno
SQL infoSupport of SQLnonoSQL-like query language, no joinsSQL-like DML and DDL statements
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
RESTful HTTP APITinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
VB.Net
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava, Javascriptno
Triggersno, except callback-events from server when changes happenednoHooksno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemSharding 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.Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes inforelationship in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonono
User concepts infoAccess controlWindows-ProfileAccess rights based on private key authentication or shared access signaturesAccess rights for users and roles; record level security configurableno

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More resources
DataFSMicrosoft Azure Table StorageOrientDBSpark SQL
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