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DBMS > Apache Phoenix vs. Firebase Realtime Database vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Firebase Realtime Database vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Embeddable relational database for web apps written in pure JavaScriptElastic, 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 processing
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgfirebase.google.com/­products/­realtime-databasegoogle.github.io/­lovefieldazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationphoenix.apache.orgfirebase.google.com/­docs/­databasegithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGoogle infoacquired by Google 2014GoogleMicrosoftApache Software Foundation
Initial release20142012201420162014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.1.12, February 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScriptC++Scala
Server operating systemsLinux
Unix
Windows
hostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyesyes
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.nonononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesnoSQL-like query language infovia JavaScript builder patternyesSQL-like DML and DDL statements
APIs and other access methodsJDBCAndroid
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
JavaScript
Objective-C
JavaScriptC#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionslimited functionality with using 'rules'noTransact SQLno
TriggersnoCallbacks are triggered when data changesUsing read-only observersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency
Foreign keys infoReferential integritynonoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDBno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyes, based on authentication and database rulesnoyesno

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More resources
Apache PhoenixFirebase Realtime DatabaseLovefieldMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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