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DBMS > Apache Spark (SQL) vs. FoundationDB vs. PostgreSQL

System Properties Comparison Apache Spark (SQL) vs. FoundationDB vs. PostgreSQL

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonFoundationDB  Xexclude from comparisonPostgreSQL  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingOrdered key-value store. Core features are complimented by layers.Widely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score21.62
Rank#29  Overall
#18  Relational DBMS
Score0.89
Rank#197  Overall
#32  Document stores
#29  Key-value stores
#92  Relational DBMS
Score674.32
Rank#4  Overall
#4  Relational DBMS
Websitespark.apache.org/­sqlgithub.com/­apple/­foundationdbwww.postgresql.org
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlapple.github.io/­foundationdbwww.postgresql.org/­docs
DeveloperApache Software FoundationFoundationDBPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release201420131989 info1989: Postgres, 1996: PostgreSQL
Current release3.5.0 ( 2.13), September 20236.2.28, November 202016.4, August 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant.
Implementation languageScalaC++C
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesschema-free infosome layers support schemasyes
Typing infopredefined data types such as float or dateyesno infosome layers support typingyes
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.noyes infospecific XML-type available, but no XML query functionality.
Secondary indexesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementssupported in specific SQL layer onlyyes infostandard with numerous extensions
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesJava
Python
R
Scala
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoin SQL-layer onlyuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate Consistency
Foreign keys infoReferential integritynoin SQL-layer onlyyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.nono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
Apache Spark (SQL)FoundationDBPostgreSQL
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