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DBMS > Geode vs. Postgres-XL vs. Solr vs. Yanza

System Properties Comparison Geode vs. Postgres-XL vs. Solr vs. Yanza

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSolr  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresA widely used distributed, scalable search engine based on Apache LuceneTime Series DBMS for IoT Applications
Primary database modelKey-value storeRelational DBMSSearch engineTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitegeode.apache.orgwww.postgres-xl.orgsolr.apache.orgyanza.com
Technical documentationgeode.apache.org/­docswww.postgres-xl.org/­documentationsolr.apache.org/­resources.html
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software FoundationYanza
Initial release20022014 infosince 2012, originally named StormDB20062015
Current release1.1, February 201710 R1, October 20189.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoMozilla public licenseOpen Source infoApache Version 2commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCJava
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Windows
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
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 infoXML type, but no XML query functionalityyesno
Secondary indexesnoyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like query language (OQL)yes infodistributed, parallel query executionSolr Parallel SQL Interfaceno
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
HTTP API
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsJava pluginsno
Triggersyes infoCache Event Listenersyesyes infoUser configurable commands triggered on index changesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodeACID infoMVCCoptimistic 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.yesnoyes
User concepts infoAccess controlAccess rights per client and object definablefine grained access rights according to SQL-standardyesno

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More resources
GeodePostgres-XLSolrYanza
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