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DBMS > Geode vs. OrigoDB vs. Solr vs. Spark SQL

System Properties Comparison Geode vs. OrigoDB vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonOrigoDB  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA fully ACID in-memory object graph databaseA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument store
Object oriented DBMS
Search engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.86
Rank#134  Overall
#24  Key-value stores
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegeode.apache.orgorigodb.comsolr.apache.orgspark.apache.org/­sql
Technical documentationgeode.apache.org/­docsorigodb.com/­docssolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Robert Friberg et alApache Software FoundationApache Software Foundation
Initial release20022009 infounder the name LiveDB20062014
Current release1.1, February 20179.6.1, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfireOpen SourceOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#JavaScala
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsyes 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.nono infocan be achieved using .NETyesno
Secondary indexesnoyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like query language (OQL)noSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
.NET Client API
HTTP API
LINQ
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesJava pluginsno
Triggersyes infoCache Event Listenersyes infoDomain Eventsyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoclient side managed; servers are not synchronizedShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynodepending on modelnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodeACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAccess rights per client and object definableRole based authorizationyesno

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More resources
GeodeOrigoDBSolrSpark SQL
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