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DBMS > Apache Phoenix vs. Firebase Realtime Database vs. Geode vs. KeyDB

System Properties Comparison Apache Phoenix vs. Firebase Realtime Database vs. Geode vs. KeyDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGeode  Xexclude from comparisonKeyDB  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.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMSDocument storeKey-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Websitephoenix.apache.orgfirebase.google.com/­products/­realtime-databasegeode.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationphoenix.apache.orgfirebase.google.com/­docs/­databasegeode.apache.org/­docsdocs.keydb.dev
DeveloperApache Software FoundationGoogle infoacquired by Google 2014Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.EQ Alpha Technology Ltd.
Initial release2014201220022019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.1, February 2017
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsLinux
Unix
Windows
hostedAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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 infoby using the Redis Search module
SQL infoSupport of SQLyesnoSQL-like query language (OQL)no
APIs and other access methodsJDBCAndroid
iOS
JavaScript API
RESTful HTTP API
Java Client API
Memcached protocol
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
JavaScript
Objective-C
.Net
All JVM based languages
C++
Groovy
Java
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresuser defined functionslimited functionality with using 'rules'user defined functionsLua
TriggersnoCallbacks are triggered when data changesyes infoCache Event Listenersno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationMulti-source replication
Source-replica replication
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
Eventual ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesyes, on a single nodeOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
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 rulesAccess rights per client and object definablesimple password-based access control and ACL

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Apache PhoenixFirebase Realtime DatabaseGeodeKeyDB
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