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DBMS > Apache Phoenix vs. MonetDB vs. Solr vs. Sphinx

System Properties Comparison Apache Phoenix vs. MonetDB vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonMonetDB  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA relational database management system that stores data in columnsA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSSearch engineSearch engine
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitephoenix.apache.orgwww.monetdb.orgsolr.apache.orgsphinxsearch.com
Technical documentationphoenix.apache.orgwww.monetdb.org/­Documentationsolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperApache Software FoundationMonetDB BVApache Software FoundationSphinx Technologies Inc.
Initial release2014200420062001
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019Dec2023 (11.49), December 20239.6.0, April 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMozilla Public License 2.0Open Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJavaC++
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyes 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 typingno
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.noyes
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLyesyes infoSQL 2003 with some extensionsSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsJDBCJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsyes, in SQL, C, RJava pluginsno
Triggersnoyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding via remote tablesShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none infoSource-replica replication available in experimental statusyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardyesno

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Apache PhoenixMonetDBSolrSphinx
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