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

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

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGeode  Xexclude from comparisonPostgres-XL  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Geode 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 Lucene
Primary database modelRelational DBMSKey-value storeRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.86
Rank#134  Overall
#24  Key-value stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitegeode.apache.orgwww.postgres-xl.orgsolr.apache.org
Technical documentationgeode.apache.org/­docswww.postgres-xl.org/­documentationsolr.apache.org/­resources.html
DeveloperDrizzle project, originally started by Brian AkerOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software Foundation
Initial release200820022014 infosince 2012, originally named StormDB2006
Current release7.2.4, September 20121.1, February 201710 R1, October 20189.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoMozilla public licenseOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaCJava
Server operating systemsFreeBSD
Linux
OS X
All 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)
Data schemeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes 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.noyes infoXML type, but no XML query functionalityyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (OQL)yes infodistributed, parallel query executionSolr Parallel SQL Interface
APIs and other access methodsJDBCJava 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
Supported programming languagesC
C++
Java
PHP
.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
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsJava plugins
Triggersno infohooks for callbacks inside the server can be used.yes infoCache Event Listenersyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeACID infoMVCCoptimistic 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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights per client and object definablefine grained access rights according to SQL-standardyes

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More resources
DrizzleGeodePostgres-XLSolr
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