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DBMS > Apache Phoenix vs. Badger vs. Drizzle vs. Solr

System Properties Comparison Apache Phoenix vs. Badger vs. Drizzle vs. Solr

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBadger  Xexclude from comparisonDrizzle  Xexclude from comparisonSolr  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value storeRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitephoenix.apache.orggithub.com/­dgraph-io/­badgersolr.apache.org
Technical documentationphoenix.apache.orggodoc.org/­github.com/­dgraph-io/­badgersolr.apache.org/­resources.html
DeveloperApache Software FoundationDGraph LabsDrizzle project, originally started by Brian AkerApache Software Foundation
Initial release2014201720082006
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.2.4, September 20129.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGNU GPLOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++Java
Server operating systemsLinux
Unix
Windows
BSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnoyesyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoyes infowith proprietary extensionsSolr Parallel SQL Interface
APIs and other access methodsJDBCJDBCJava API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
GoC
C++
Java
PHP
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsnonoJava plugins
Triggersnonono infohooks for callbacks inside the server can be used.yes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencynoneEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDoptimistic locking
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.yesnoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoPluggable authentication mechanisms infoe.g. LDAP, HTTPyes

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More resources
Apache PhoenixBadgerDrizzleSolr
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

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16 August 2018, Microsoft

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