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

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

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemA Wide Column Store for rapid development using massive semi-structured datasetsSpark 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 modelRelational DBMSWide column storeRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitewww.4d.comazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sqlwww.tigergraph.com
Technical documentationdeveloper.4d.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
Developer4D, IncMicrosoftApache Software Foundation
Initial release1984201220142017
Current releasev20, April 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
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 languageScalaC++
Server operating systemsOS X
Windows
hostedLinux
OS X
Windows
Linux
Data schemeyesschema-freeyesyes
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.yesnonono
Secondary indexesyesnono
SQL infoSupport of SQLyes infoclose to SQL 92noSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
RESTful HTTP APIJDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages4D proprietary IDE
PHP
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresyesnonoyes
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceyes, 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.none
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 integrityyesnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingnoACID
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.nononono
User concepts infoAccess controlUsers and groupsAccess rights based on private key authentication or shared access signaturesnoRole-based access control

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More resources
4D infoformer name: 4th DimensionMicrosoft Azure Table StorageSpark SQLTigerGraph
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