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

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

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonIRONdb  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb 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 processesA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA 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 storeTime Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.92
Rank#131  Overall
#23  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegeode.apache.orgwww.circonus.com/solutions/time-series-database/solr.apache.orgspark.apache.org/­sql
Technical documentationgeode.apache.org/­docsdocs.circonus.com/irondb/category/getting-startedsolr.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.Circonus LLC.Apache Software FoundationApache Software Foundation
Initial release2002201720062014
Current release1.1, February 2017V0.10.20, January 20189.6.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen 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 and C++JavaScala
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyes 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 indexesnonoyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like query language (OQL)SQL-like query language (Circonus Analytics Query Language: CAQL)Solr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
HTTP APIJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.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 functionsyes, in LuaJava pluginsno
Triggersyes infoCache Event Listenersnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationconfigurable replication factor, datacenter awareyesnone
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 ConsistencyImmediate consistency per node, eventual consistency across nodesEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodenooptimistic 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.yesnoyesno
User concepts infoAccess controlAccess rights per client and object definablenoyesno

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More resources
GeodeIRONdbSolrSpark SQL
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