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DBMS > Cubrid vs. GigaSpaces vs. GridGain vs. Solr

System Properties Comparison Cubrid vs. GigaSpaces vs. GridGain vs. Solr

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGridGain  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsGridGain is an in-memory computing platform, built on Apache IgniteA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Key-value store
Relational DBMS
Search engine
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitecubrid.com (korean)
cubrid.org (english)
www.gigaspaces.comwww.gridgain.comsolr.apache.org
Technical documentationcubrid.org/­manualsdocs.gigaspaces.com/­latest/­landing.htmlwww.gridgain.com/­docs/­index.htmlsolr.apache.org/­resources.html
DeveloperCUBRID Corporation, CUBRID FoundationGigaspaces TechnologiesGridGain Systems, Inc.Apache Software Foundation
Initial release2008200020072006
Current release11.0, January 202115.5, September 2020GridGain 8.5.19.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availablecommercialOpen 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, C++, JavaJava, C++, .NetJava, C++, .NetJava
Server operating systemsLinux
Windows
Linux
macOS
Solaris
Windows
Linux
OS X
Solaris
Windows
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.nono infoXML can be used for describing objects metadatayesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesSQL-99 for query and DML statementsANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C++
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresyesyes (compute grid and cache interceptors can be used instead)Java plugins
Triggersyesyes, event driven architectureyes (cache interceptors and events)yes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyes (compute grid and hadoop accelerator)spark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDoptimistic 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.noyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlSecurity Hooks for custom implementationsyes

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More resources
CubridGigaSpacesGridGainSolr
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