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DBMS > 4D vs. Apache Impala vs. PostGIS vs. Spark SQL

System Properties Comparison 4D vs. Apache Impala vs. PostGIS vs. Spark SQL

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonApache Impala  Xexclude from comparisonPostGIS  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAnalytic DBMS for HadoopSpatial extension of PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSSpatial DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score21.72
Rank#29  Overall
#1  Spatial DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.4d.comimpala.apache.orgpostgis.netspark.apache.org/­sql
Technical documentationdeveloper.4d.comimpala.apache.org/­impala-docs.htmlpostgis.net/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation
Initial release1984201320052014
Current releasev20, April 20234.1.0, June 20223.4.2, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGPL v2.0Open 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 languageC++CScala
Server operating systemsOS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like DML and DDL statementsyesSQL-like DML and DDL statements
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
ODBC
JDBC
ODBC
Supported programming languages4D proprietary IDE
PHP
All languages supporting JDBC/ODBCJava
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceuser defined functionsno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infobased on PostgreSQLyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factoryes infobased on PostgreSQLnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.nononono
User concepts infoAccess controlUsers and groupsAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes infobased on PostgreSQLno

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More resources
4D infoformer name: 4th DimensionApache ImpalaPostGISSpark SQL
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