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DBMS > Firebase Realtime Database vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Valentina Server

System Properties Comparison Firebase Realtime Database vs. Oracle Berkeley DB vs. Spark SQL vs. TerarkDB vs. Valentina Server

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparisonValentina Server  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.Widely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBObject-relational database and reports server
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­bytedance/­terarkdbwww.valentina-db.net
Technical documentationfirebase.google.com/­docs/­databasedocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperGoogle infoacquired by Google 2014Oracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationByteDance, originally TerarkParadigma Software
Initial release20121994201420161999
Current release18.1.40, May 20203.5.0 ( 2.13), September 20235.7.5
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Source infoApache 2.0commercial inforestricted open source version availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesnoyes
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.noyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLnoyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsnoyes
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
C++ API
Java API
ODBC
Supported programming languagesJava
JavaScript
Objective-C
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
C++
Java
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored procedureslimited functionality with using 'rules'nononoyes
TriggersCallbacks are triggered when data changesyes infoonly for the SQL APInonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlyes, based on authentication and database rulesnononofine grained access rights according to SQL-standard

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More resources
Firebase Realtime DatabaseOracle Berkeley DBSpark SQLTerarkDBValentina Server
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