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DBMS > Cubrid vs. Firebase Realtime Database vs. Ignite vs. Solr

System Properties Comparison Cubrid vs. Firebase Realtime Database vs. Ignite vs. Solr

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonIgnite  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSDocument storeKey-value store
Relational DBMS
Search engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#169  Overall
#78  Relational DBMS
Score15.00
Rank#39  Overall
#6  Document stores
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Websitecubrid.com (korean)
cubrid.org (english)
firebase.google.com/­products/­realtime-databaseignite.apache.orgsolr.apache.org
Technical documentationcubrid.org/­manualsfirebase.google.com/­docs/­databaseapacheignite.readme.io/­docssolr.apache.org/­resources.html
DeveloperCUBRID Corporation, CUBRID FoundationGoogle infoacquired by Google 2014Apache Software FoundationApache Software Foundation
Initial release2008201220152006
Current release11.0, January 2021Apache Ignite 2.69.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaC++, Java, .NetJava
Server operating systemsLinux
Windows
hostedLinux
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.nonoyesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
Android
iOS
JavaScript API
RESTful HTTP API
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
Java
JavaScript
Objective-C
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 Procedureslimited functionality with using 'rules'yes (compute grid and cache interceptors can be used instead)Java plugins
TriggersyesCallbacks are triggered when data changesyes (cache interceptors and events)yes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (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 ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDoptimistic 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.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesSecurity Hooks for custom implementationsyes

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CubridFirebase Realtime DatabaseIgniteSolr
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