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DBMS > 4D vs. LeanXcale vs. Postgres-XL vs. Spark SQL

System Properties Comparison 4D vs. LeanXcale vs. Postgres-XL vs. Spark SQL

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonLeanXcale  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.4d.comwww.leanxcale.comwww.postgres-xl.orgspark.apache.org/­sql
Technical documentationdeveloper.4d.comwww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncLeanXcaleApache Software Foundation
Initial release198420152014 infosince 2012, originally named StormDB2014
Current releasev20, April 202310 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScala
Server operating systemsOS X
Windows
Linux
macOS
Linux
OS X
Windows
Data schemeyesyesyesyes
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.yesyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesno
SQL infoSupport of SQLyes infoclose to SQL 92yes infothrough Apache Derbyyes infodistributed, parallel query executionSQL-like DML and DDL statements
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languages4D proprietary IDE
PHP
C
Java
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoMVCCno
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 groupsfine grained access rights according to SQL-standardno

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More resources
4D infoformer name: 4th DimensionLeanXcalePostgres-XLSpark SQL
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