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DBMS > Firebase Realtime Database vs. IBM Db2 Event Store vs. Ignite vs. Solr

System Properties Comparison Firebase Realtime Database vs. IBM Db2 Event Store vs. Ignite vs. Solr

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonIBM Db2 Event Store  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.Distributed Event Store optimized for Internet of Things use casesApache 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 storeEvent Store
Time Series DBMS
Key-value store
Relational DBMS
Search engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitefirebase.google.com/­products/­realtime-databasewww.ibm.com/­products/­db2-event-storeignite.apache.orgsolr.apache.org
Technical documentationfirebase.google.com/­docs/­databasewww.ibm.com/­docs/­en/­db2-event-storeapacheignite.readme.io/­docssolr.apache.org/­resources.html
DeveloperGoogle infoacquired by Google 2014IBMApache Software FoundationApache Software Foundation
Initial release2012201720152006
Current release2.0Apache Ignite 2.69.6.0, April 2024
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen 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 languageC and C++C++, Java, .NetJava
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionLinux
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.nonoyesyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimeANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL Interface
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
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
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
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'yesyes (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 nodesActive-active shard 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 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 datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyes, based on authentication and database rulesfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsyes

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