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DBMS > Apache Phoenix vs. Geode vs. Solr vs. Transbase

System Properties Comparison Apache Phoenix vs. Geode vs. Solr vs. Transbase

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGeode  Xexclude from comparisonSolr  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA widely used distributed, scalable search engine based on Apache LuceneA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSKey-value storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitephoenix.apache.orggeode.apache.orgsolr.apache.orgwww.transaction.de/­en/­products/­transbase.html
Technical documentationphoenix.apache.orggeode.apache.org/­docssolr.apache.org/­resources.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software FoundationTransaction Software GmbH
Initial release2014200220061987
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.1, February 20179.6.0, April 2024Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache Version 2commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaC and C++
Server operating systemsLinux
Unix
Windows
All OS with a Java VM infothe JDK (8 or later) is also requiredAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
macOS
Solaris
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 indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSQL-like query language (OQL)Solr Parallel SQL Interfaceyes
APIs and other access methodsJDBCJava Client API
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsJava pluginsyes
Triggersnoyes infoCache Event Listenersyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationyesSource-replica replication
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 ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeoptimistic lockingyes
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.yesyesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights per client and object definableyesfine grained access rights according to SQL-standard

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More resources
Apache PhoenixGeodeSolrTransbase
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