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DBMS > Apache Phoenix vs. FoundationDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. FoundationDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFoundationDB  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseOrdered 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 modelRelational DBMSDocument 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
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score1.07
Rank#188  Overall
#31  Document stores
#28  Key-value stores
#86  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orggithub.com/­apple/­foundationdbspark.apache.org/­sql
Technical documentationphoenix.apache.orgapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationFoundationDBApache Software Foundation
Initial release201420132014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20196.2.28, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open 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 languageJavaC++Scala
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-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.nono
Secondary indexesyesnono
SQL infoSupport of SQLyessupported in specific SQL layer onlySQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsin SQL-layer onlyno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyLinearizable consistency
Foreign keys infoReferential integritynoin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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 controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynono

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More resources
Apache PhoenixFoundationDBSpark SQL
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