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DBMS > 4D vs. Linter vs. Solr vs. Spark SQL vs. TimesTen

System Properties Comparison 4D vs. Linter vs. Solr vs. Spark SQL vs. TimesTen

Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonLinter  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemRDBMS for high security requirementsA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.4d.comlinter.rusolr.apache.orgspark.apache.org/­sqlwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdeveloper.4d.comsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.oracle.com/­database/­timesten-18.1
Developer4D, Increlex.ruApache Software FoundationApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release19841990200620141998
Current releasev20, April 20239.6.0, April 20243.5.0 ( 2.13), September 202311 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaScala
Server operating systemsOS X
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyesyes
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.yesnoyesnono
Secondary indexesyesyesyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLyes infoclose to SQL 92yesSolr Parallel SQL InterfaceSQL-like DML and DDL statementsyes
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Java API
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languages4D proprietary IDE
PHP
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyesyes infoproprietary syntax with the possibility to convert from PL/SQLJava pluginsnoPL/SQL
Triggersyesyesyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlUsers and groupsfine grained access rights according to SQL-standardyesnofine grained access rights according to SQL-standard

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More resources
4D infoformer name: 4th DimensionLinterSolrSpark SQLTimesTen
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