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DBMS > Apache Phoenix vs. Percona Server for MongoDB vs. Solr vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Percona Server for MongoDB vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA drop-in replacement for MongoDB Community Edition with enterprise-grade features.A widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score0.55
Rank#253  Overall
#39  Document stores
Score44.28
Rank#24  Overall
#3  Search engines
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.percona.com/­mongodb/­software/­percona-server-for-mongodbsolr.apache.orgspark.apache.org/­sql
Technical documentationphoenix.apache.orgdocs.percona.com/­percona-distribution-for-mongodbsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationPerconaApache Software FoundationApache Software Foundation
Initial release2014201520062014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.4.10-2.10, November 20179.5.0, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPL Version 2Open Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaScala
Server operating systemsLinux
Unix
Windows
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic 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.nonoyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLyesnoSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsJDBCproprietary protocol using JSONJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsJavaScriptJava pluginsno
Triggersnonoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infovia In-Memory Engineyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users and rolesyesno

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More resources
Apache PhoenixPercona Server for MongoDBSolrSpark SQL
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