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DBMS > 4D vs. Microsoft Azure Table Storage vs. OrigoDB vs. Spark SQL

System Properties Comparison 4D vs. Microsoft Azure Table Storage vs. OrigoDB vs. Spark SQL

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemA Wide Column Store for rapid development using massive semi-structured datasetsA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSWide column storeDocument store
Object oriented DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.06
Rank#380  Overall
#50  Document stores
#19  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.4d.comazure.microsoft.com/­en-us/­services/­storage/­tablesorigodb.comspark.apache.org/­sql
Technical documentationdeveloper.4d.comorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncMicrosoftRobert Friberg et alApache Software Foundation
Initial release198420122009 infounder the name LiveDB2014
Current releasev20, April 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen 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 languageC#Scala
Server operating systemsOS X
Windows
hostedLinux
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsyes
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.yesnono infocan be achieved using .NETno
Secondary indexesyesnoyesno
SQL infoSupport of SQLyes infoclose to SQL 92nonoSQL-like DML and DDL statements
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
RESTful HTTP API.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languages4D proprietary IDE
PHP
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyesno
Triggersyesnoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnodepending on modelno
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 persistentyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlUsers and groupsAccess rights based on private key authentication or shared access signaturesRole based authorizationno

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More resources
4D infoformer name: 4th DimensionMicrosoft Azure Table StorageOrigoDBSpark SQL
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