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

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

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  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 networksSpark SQL is a component on top of 'Spark Core' for structured data processingA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.80
Rank#111  Overall
#55  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score1.59
Rank#162  Overall
#14  Time Series DBMS
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositoryspark.apache.org/­sqlvictoriametrics.com
Technical documentationdeveloper.4d.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
Developer4D, IncAtos Convergence CreatorsApache Software FoundationVictoriaMetrics
Initial release1984201620142018
Current releasev20, April 202317033.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaGo
Server operating systemsOS X
Windows
LinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesSchema and schema-less with LDAP viewsyes
Typing infopredefined data types such as float or dateyesoptionalyes
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.yesyesnono
Secondary indexesyesyesno
SQL infoSupport of SQLyes infoclose to SQL 92noSQL-like DML and DDL statementsno
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
LDAPJDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languages4D proprietary IDE
PHP
All languages with LDAP bindingsJava
Python
R
Scala
Server-side scripts infoStored proceduresyesnonono
Triggersyesyesnono
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 replicationyesnoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnono
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.noyesnono
User concepts infoAccess controlUsers and groupsLDAP bind authenticationno

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More resources
4D infoformer name: 4th DimensionAtos Standard Common RepositorySpark SQLVictoriaMetrics
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