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DBMS > Apache Phoenix vs. Firebase Realtime Database vs. Quasardb vs. Vitess

System Properties Comparison Apache Phoenix vs. Firebase Realtime Database vs. Quasardb vs. Vitess

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonQuasardb  Xexclude from comparisonVitess  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.Distributed, high-performance timeseries databaseScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitephoenix.apache.orgfirebase.google.com/­products/­realtime-databasequasar.aivitess.io
Technical documentationphoenix.apache.orgfirebase.google.com/­docs/­databasedoc.quasar.ai/­mastervitess.io/­docs
DeveloperApache Software FoundationGoogle infoacquired by Google 2014quasardbThe Linux Foundation, PlanetScale
Initial release2014201220092013
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.14.1, January 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Go
Server operating systemsLinux
Unix
Windows
hostedBSD
Linux
OS X
Windows
Docker
Linux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes
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.nonono
Secondary indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLyesnoSQL-like query languageyes infowith proprietary extensions
APIs and other access methodsJDBCAndroid
iOS
JavaScript API
RESTful HTTP API
HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
JavaScript
Objective-C
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionslimited functionality with using 'rules'noyes infoproprietary syntax
TriggersnoCallbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication with selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnowith Hadoop integrationno
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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoTransient modeyes
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 rulesCryptographically strong user authentication and audit trailUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache PhoenixFirebase Realtime DatabaseQuasardbVitess
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