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DBMS > 4D vs. Spark SQL vs. Teradata Aster

System Properties Comparison 4D vs. Spark SQL vs. Teradata Aster

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
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 systemSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.68
Rank#110  Overall
#54  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.4d.comspark.apache.org/­sql
Technical documentationdeveloper.4d.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncApache Software FoundationTeradata
Initial release198420142005
Current releasev20, April 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScala
Server operating systemsOS X
Windows
Linux
OS X
Windows
Linux
Data schemeyesyesFlexible 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 dateyesyesyes
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.yesnoyes infoin Aster File Store
Secondary indexesyesnoyes
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like DML and DDL statementsyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages4D proprietary IDE
PHP
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesnoR packages
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneyes 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 methodsnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlUsers and groupsnofine grained access rights according to SQL-standard

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More resources
4D infoformer name: 4th DimensionSpark SQLTeradata Aster
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