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DBMS > Firebase Realtime Database vs. Google Cloud Firestore vs. MarkLogic vs. Spark SQL vs. SwayDB

System Properties Comparison Firebase Realtime Database vs. Google Cloud Firestore vs. MarkLogic vs. Spark SQL vs. SwayDB

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  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.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Operational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelDocument storeDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
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
Score7.85
Rank#51  Overall
#8  Document stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitefirebase.google.com/­products/­realtime-databasefirebase.google.com/­products/­firestorewww.marklogic.comspark.apache.org/­sqlswaydb.simer.au
Technical documentationfirebase.google.com/­docs/­databasefirebase.google.com/­docs/­firestoredocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogle infoacquired by Google 2014GoogleMarkLogic Corp.Apache Software FoundationSimer Plaha
Initial release20122017200120142018
Current release11.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ScalaScala
Server operating systemshostedhostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-free infoSchema can be enforcedyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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 indexesyesyesyesnono
SQL infoSupport of SQLnonoyes infoSQL92SQL-like DML and DDL statementsno
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
Android
gRPC (using protocol buffers) API
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
Supported programming languagesJava
JavaScript
Objective-C
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored procedureslimited functionality with using 'rules'yes, Firebase Rules & Cloud Functionsyes infovia XQuery or JavaScriptnono
TriggersCallbacks are triggered when data changesyes, with Cloud Functionsyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowyes 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 integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesyesACID infocan act as a resource manager in an XA/JTA transactionnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yes, with Range Indexesnoyes
User concepts infoAccess controlyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Role-based access control at the document and subdocument levelsnono

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More resources
Firebase Realtime DatabaseGoogle Cloud FirestoreMarkLogicSpark SQLSwayDB
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