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DBMS > Apache Phoenix vs. Fauna vs. Spark SQL

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.57
Rank#93  Overall
#49  Relational DBMS
Score1.63
Rank#139  Overall
#23  Document stores
#12  Graph DBMS
#68  Relational DBMS
#9  Time Series DBMS
Score23.33
Rank#33  Overall
#19  Relational DBMS
Websitephoenix.apache.orgfauna.comspark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.fauna.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationFauna, Inc.Apache Software Foundation
Initial release201420142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.2.0, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaScala
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLyesnoSQL-like DML and DDL statements
APIs and other access methodsJDBCRESTful HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyIdentity management, authentication, and access controlno

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More resources
Apache PhoenixFauna infopreviously named FaunaDBSpark SQL
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Recent citations in the news

Apache Phoenix Now HBase 2.0 Compatible
20 July 2018, iProgrammer

Developing Python Applications Against Apache Phoenix (HBase)
30 September 2016, DZone News

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