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DBMS > FoundationDB vs. Geode vs. Spark SQL

System Properties Comparison FoundationDB vs. Geode vs. Spark SQL

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonGeode  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesSpark 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
Key-value storeRelational 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
Score1.92
Rank#131  Overall
#23  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­apple/­foundationdbgeode.apache.orgspark.apache.org/­sql
Technical documentationapple.github.io/­foundationdbgeode.apache.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFoundationDBOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software Foundation
Initial release201320022014
Current release6.2.28, November 20201.1, February 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScala
Server operating systemsLinux
OS X
Windows
All OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Windows
Data schemeschema-free infosome layers support schemasschema-freeyes
Typing infopredefined data types such as float or dateno infosome layers support 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.nono
Secondary indexesnonono
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like query language (OQL)SQL-like DML and DDL statements
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
All JVM based languages
C++
Groovy
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresin SQL-layer onlyuser defined functionsno
Triggersnoyes infoCache Event Listenersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyEventual Consistency
Foreign keys infoReferential integrityin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeno
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.yesno
User concepts infoAccess controlnoAccess rights per client and object definableno

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FoundationDBGeodeSpark SQL
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