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DBMS > FoundationDB vs. Spark SQL

System Properties Comparison FoundationDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonSpark SQL  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionOrdered key-value store. Core features are complimented by layers.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­apple/­foundationdbspark.apache.org/­sql
Technical documentationapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFoundationDBApache Software Foundation
Initial release20132014
Current release6.2.28, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-free infosome layers support schemasyes
Typing infopredefined data types such as float or dateno 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.no
Secondary indexesnono
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresin SQL-layer onlyno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistency
Foreign keys infoReferential integrityin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlnono

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More resources
FoundationDBSpark SQL
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