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DBMS > FoundationDB vs. Impala vs. Spark SQL

System Properties Comparison FoundationDB vs. Impala vs. Spark SQL

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonImpala  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.Analytic DBMS for HadoopSpark 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 DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.60
Rank#167  Overall
#29  Document stores
#28  Key-value stores
#81  Relational DBMS
Score18.70
Rank#37  Overall
#23  Relational DBMS
Score19.74
Rank#36  Overall
#22  Relational DBMS
Websitegithub.com/­apple/­foundationdbwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlspark.apache.org/­sql
Technical documentationapple.github.io/­foundationdbdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFoundationDBClouderaApache Software Foundation
Initial release201320132014
Current release6.2.28, November 20204.1.0, June 20223.3.0 ( 2.13), June 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open 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++C++Scala
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeschema-free infosome layers support schemasyesyes
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 indexesnoyesno
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
All languages supporting JDBC/ODBCJava
Python
R
Scala
Server-side scripts infoStored proceduresin SQL-layer onlyyes infouser defined functions and integration of map-reduceno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduce
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 dataACIDnono
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 controlnoAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno

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More resources
FoundationDBImpalaSpark SQL
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