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DBMS > Badger vs. Firebase Realtime Database vs. Microsoft Azure Table Storage vs. Solr

System Properties Comparison Badger vs. Firebase Realtime Database vs. Microsoft Azure Table Storage vs. Solr

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value storeDocument storeWide column storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score13.64
Rank#39  Overall
#6  Document stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitegithub.com/­dgraph-io/­badgerfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerfirebase.google.com/­docs/­databasesolr.apache.org/­resources.html
DeveloperDGraph LabsGoogle infoacquired by Google 2014MicrosoftApache Software Foundation
Initial release2017201220122006
Current release9.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenoyesyesyes 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.nononoyes
Secondary indexesnoyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnononoSolr Parallel SQL Interface
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesGoJava
JavaScript
Objective-C
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'noJava plugins
TriggersnoCallbacks are triggered when data changesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesoptimistic lockingoptimistic 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.nonoyes
User concepts infoAccess controlnoyes, based on authentication and database rulesAccess rights based on private key authentication or shared access signaturesyes

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More resources
BadgerFirebase Realtime DatabaseMicrosoft Azure Table StorageSolr
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