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

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

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonLevelDB  Xexclude from comparisonOracle Berkeley DB  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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesWidely 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 MongoDB
Primary database modelDocument storeKey-value storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score2.35
Rank#111  Overall
#19  Key-value 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
Websitefirebase.google.com/­products/­realtime-databasegithub.com/­google/­leveldbwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationfirebase.google.com/­docs/­databasegithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperGoogle infoacquired by Google 2014GoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationByteDance, originally Terark
Initial release20122011199420142016
Current release1.23, February 202118.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infocommercial license availableOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemshostedIllumos
Linux
OS X
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnonoyesno
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.nonoyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesnoyesnono
SQL infoSupport of SQLnonoyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsno
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
C++ API
Java API
Supported programming languagesJava
JavaScript
Objective-C
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.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
Server-side scripts infoStored procedureslimited functionality with using 'rules'nononono
TriggersCallbacks are triggered when data changesnoyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesnonenoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-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
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyes, based on authentication and database rulesnononono

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More resources
Firebase Realtime DatabaseLevelDBOracle Berkeley DBSpark SQLTerarkDB
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