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DBMS > Firebase Realtime Database vs. Microsoft Azure Synapse Analytics vs. Spark SQL vs. Vitess vs. WakandaDB

System Properties Comparison Firebase Realtime Database vs. Microsoft Azure Synapse Analytics vs. Spark SQL vs. Vitess vs. WakandaDB

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparisonVitess  Xexclude from comparisonWakandaDB  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.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processingScalable, distributed, cloud-native DBMS, extending MySQLWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitefirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sqlvitess.iowakanda.github.io
Technical documentationfirebase.google.com/­docs/­databasedocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvitess.io/­docswakanda.github.io/­doc
DeveloperGoogle infoacquired by Google 2014MicrosoftApache Software FoundationThe Linux Foundation, PlanetScaleWakanda SAS
Initial release20122016201420132012
Current release3.5.0 ( 2.13), September 202315.0.2, December 20222.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses availableOpen Source infoAGPLv3, extended commercial license available
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++ScalaGoC++, JavaScript
Server operating systemshostedhostedLinux
OS X
Windows
Docker
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsyes infowith proprietary extensionsno
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
RESTful HTTP API
Supported programming languagesJava
JavaScript
Objective-C
C#
Java
PHP
Java
Python
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
JavaScript
Server-side scripts infoStored procedureslimited functionality with using 'rules'Transact SQLnoyes infoproprietary syntaxyes
TriggersCallbacks are triggered when data changesnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningyes, utilizing Spark CoreShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication
Source-replica replication
none
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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnoACID at shard levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes
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.noyesno
User concepts infoAccess controlyes, based on authentication and database rulesyesnoUsers with fine-grained authorization concept infono user groups or rolesyes

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More resources
Firebase Realtime DatabaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQLVitessWakandaDB
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