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DBMS > Firebase Realtime Database vs. Oracle Berkeley DB vs. Percona Server for MySQL vs. Spark SQL vs. TerarkDB

System Properties Comparison Firebase Realtime Database vs. Oracle Berkeley DB vs. Percona Server for MySQL vs. Spark SQL vs. TerarkDB

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPercona Server for MySQL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  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 storeEnhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.Spark 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 MongoDB
Primary database modelDocument storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMSKey-value store
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
Score2.03
Rank#122  Overall
#57  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitefirebase.google.com/­products/­realtime-databasewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.percona.com/­software/­mysql-database/­percona-serverspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationfirebase.google.com/­docs/­databasedocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.percona.com/­downloads/­Percona-Server-LATESTspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperGoogle infoacquired by Google 2014Oracle infooriginally developed by Sleepycat, which was acquired by OraclePerconaApache Software FoundationByteDance, originally Terark
Initial release20121994200820142016
Current release18.1.40, May 20208.0.36-28, 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Source infoGPL version 2Open Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, C++ (depending on the Berkeley DB edition)C and C++ScalaC++
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
LinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesno
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 editionyesnono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLnoyes infoSQL interfaced based on SQLite is availableyesSQL-like DML and DDL statementsno
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
C++ API
Java API
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
Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored procedureslimited functionality with using 'rules'noyesnono
TriggersCallbacks are triggered when data changesyes infoonly for the SQL APIyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
XtraDB Cluster
nonenone
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
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyesnoyes
User concepts infoAccess controlyes, based on authentication and database rulesnoUsers with fine-grained authorization concept infono user groups or rolesnono

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More resources
Firebase Realtime DatabaseOracle Berkeley DBPercona Server for MySQLSpark SQLTerarkDB
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