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DBMS > 4D vs. Atos Standard Common Repository vs. Databricks vs. RDF4J vs. Teradata Aster

System Properties Comparison 4D vs. Atos Standard Common Repository vs. Databricks vs. RDF4J vs. Teradata Aster

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTeradata Aster  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore 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 networksThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Key-value store
Document store
Relational DBMS
RDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.4d.comatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comrdf4j.org
Technical documentationdeveloper.4d.comdocs.databricks.comrdf4j.org/­documentation
Developer4D, IncAtos Convergence CreatorsDatabricksSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Teradata
Initial release19842016201320042005
Current releasev20, April 20231703
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsOS X
Windows
LinuxhostedLinux
OS X
Unix
Windows
Linux
Data schemeyesSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yes infoRDF SchemasFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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.yesyesyesyes infoin Aster File Store
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyes infoclose to SQL 92nowith Databricks SQLnoyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
LDAPJDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages4D proprietary IDE
PHP
All languages with LDAP bindingsPython
R
Scala
Java
PHP
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesnouser defined functions and aggregatesyesR packages
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesyesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
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 authenticationnofine grained access rights according to SQL-standard
More information provided by the system vendor
4D infoformer name: 4th DimensionAtos Standard Common RepositoryDatabricksRDF4J infoformerly known as SesameTeradata Aster
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
4D infoformer name: 4th DimensionAtos Standard Common RepositoryDatabricksRDF4J infoformerly known as SesameTeradata Aster
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