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DBMS > Firebase Realtime Database vs. LevelDB vs. MarkLogic vs. Sadas Engine vs. Spark SQL

System Properties Comparison Firebase Realtime Database vs. LevelDB vs. MarkLogic vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonLevelDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  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 valuesOperational and transactional Enterprise NoSQL databaseSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeKey-value storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMS
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
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasegithub.com/­google/­leveldbwww.marklogic.comwww.sadasengine.comspark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­databasegithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.marklogic.comwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogle infoacquired by Google 2014GoogleMarkLogic Corp.SADAS s.r.l.Apache Software Foundation
Initial release20122011200120062014
Current release1.23, February 202111.0, December 20228.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSDcommercial inforestricted free version is availablecommercial infofree trial version availableOpen Source infoApache 2.0
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++C++Scala
Server operating systemshostedIllumos
Linux
OS X
Windows
Linux
OS X
Windows
AIX
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonoyesnono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLnonoyes infoSQL92yesSQL-like DML and DDL statements
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesJava
JavaScript
Objective-C
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored procedureslimited functionality with using 'rules'noyes infovia XQuery or JavaScriptnono
TriggersCallbacks are triggered when data changesnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yes, with Range Indexesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlyes, based on authentication and database rulesnoRole-based access control at the document and subdocument levelsAccess rights for users, groups and roles according to SQL-standardno

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More resources
Firebase Realtime DatabaseLevelDBMarkLogicSadas EngineSpark SQL
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