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DBMS > 4D vs. FatDB vs. Spark SQL vs. STSdb

System Properties Comparison 4D vs. FatDB vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionApplication development environment with integrated database management systemA .NET NoSQL DBMS that can integrate with and extend SQL Server.Spark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.4d.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdeveloper.4d.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncFatCloudApache Software FoundationSTS Soft SC
Initial release1984201220142011
Current releasev20, April 20233.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#ScalaC#
Server operating systemsOS X
Windows
WindowsLinux
OS X
Windows
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)
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.yesno
Secondary indexesyesyesnono
SQL infoSupport of SQLyes infoclose to SQL 92no infoVia inetgration in SQL ServerSQL-like DML and DDL statementsno
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
.NET Client API
Supported programming languages4D proprietary IDE
PHP
C#Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresyesyes infovia applicationsnono
Triggersyesyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.nono
User concepts infoAccess controlUsers and groupsno infoCan implement custom security layer via applicationsnono

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More resources
4D infoformer name: 4th DimensionFatDBSpark SQLSTSdb
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