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

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

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAmazon Aurora  Xexclude from comparisonAtos Standard Common Repository  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 systemMySQL and PostgreSQL compatible cloud service by AmazonHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.4d.comaws.amazon.com/­rds/­auroraatos.net/en/convergence-creators/portfolio/standard-common-repositoryspark.apache.org/­sql
Technical documentationdeveloper.4d.comdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncAmazonAtos Convergence CreatorsApache Software Foundation
Initial release1984201520162014
Current releasev20, April 202317033.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemsOS X
Windows
hostedLinuxLinux
OS X
Windows
Data schemeyesyesSchema and schema-less with LDAP viewsyes
Typing infopredefined data types such as float or dateyesyesoptionalyes
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.yesyesyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes infoclose to SQL 92yesnoSQL-like DML and DDL statements
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
ADO.NET
JDBC
ODBC
LDAPJDBC
ODBC
Supported programming languages4D proprietary IDE
PHP
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages with LDAP bindingsJava
Python
R
Scala
Server-side scripts infoStored proceduresyesyesnono
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningSharding infocell divisionyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic execution of specific operationsno
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.noyesyesno
User concepts infoAccess controlUsers and groupsfine grained access rights according to SQL-standardLDAP bind authenticationno

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More resources
4D infoformer name: 4th DimensionAmazon AuroraAtos Standard Common RepositorySpark SQL
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