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DBMS > 4D vs. Atos Standard Common Repository vs. RDFox vs. Spark SQL

System Properties Comparison 4D vs. Atos Standard Common Repository vs. RDFox vs. Spark SQL

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionApplication development environment with integrated database management systemHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksHigh performance knowledge graph and semantic reasoning engineSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Key-value store
Graph DBMS
RDF store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.oxfordsemantic.techspark.apache.org/­sql
Technical documentationdeveloper.4d.comdocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncAtos Convergence CreatorsOxford Semantic TechnologiesApache Software Foundation
Initial release1984201620172014
Current releasev20, April 202317036.0, Septermber 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Scala
Server operating systemsOS X
Windows
LinuxLinux
macOS
Windows
Linux
OS X
Windows
Data schemeyesSchema and schema-less with LDAP viewsyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.yesyesno
Secondary indexesyesyesno
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
LDAPRESTful HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languages4D proprietary IDE
PHP
All languages with LDAP bindingsC
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnono
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesreplication via a shared file systemnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDno
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.noyesyesno
User concepts infoAccess controlUsers and groupsLDAP bind authenticationRoles, resources, and access typesno

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More resources
4D infoformer name: 4th DimensionAtos Standard Common RepositoryRDFoxSpark SQL
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