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

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

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonHive  Xexclude from comparisonIgnite  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.data warehouse software for querying and managing large distributed datasets, built on HadoopApache 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 modelDocument storeRelational DBMSKey-value store
Relational DBMS
Search engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.00
Rank#39  Overall
#6  Document stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Websitefirebase.google.com/­products/­realtime-databasehive.apache.orgignite.apache.orgsolr.apache.org
Technical documentationfirebase.google.com/­docs/­databasecwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docssolr.apache.org/­resources.html
DeveloperGoogle infoacquired by Google 2014Apache Software Foundation infoinitially developed by FacebookApache Software FoundationApache Software Foundation
Initial release2012201220152006
Current release3.1.3, April 2022Apache Ignite 2.69.5.0, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .NetJava
Server operating systemshostedAll OS with a Java VMLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyesyes 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.noyesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL Interface
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
Supported programming languagesJava
JavaScript
Objective-C
C++
Java
PHP
Python
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 procedureslimited functionality with using 'rules'yes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)Java plugins
TriggersCallbacks are triggered when data changesnoyes (cache interceptors and events)yes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes (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 systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDoptimistic 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.yesyes
User concepts infoAccess controlyes, based on authentication and database rulesAccess rights for users, groups and rolesSecurity Hooks for custom implementationsyes

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More resources
Firebase Realtime DatabaseHiveIgniteSolr
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