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DBMS > Firebase Realtime Database vs. Hazelcast vs. InterSystems Caché vs. KeyDB

System Properties Comparison Firebase Realtime Database vs. Hazelcast vs. InterSystems Caché vs. KeyDB

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonHazelcast  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonKeyDB  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A widely adopted in-memory data gridA multi-model DBMS and application serverAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelDocument storeKey-value storeKey-value store
Object oriented DBMS
Relational DBMS
Key-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.64
Rank#39  Overall
#6  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Websitefirebase.google.com/­products/­realtime-databasehazelcast.comwww.intersystems.com/­products/­cachegithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationfirebase.google.com/­docs/­databasehazelcast.org/­imdg/­docsdocs.intersystems.comdocs.keydb.dev
DeveloperGoogle infoacquired by Google 2014HazelcastInterSystemsEQ Alpha Technology Ltd.
Initial release2012200819972019
Current release5.3.6, November 20232018.1.4, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freedepending on used data modelschema-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.noyes infothe object must implement a serialization strategyyesno
Secondary indexesyesyesyesyes infoby using the Redis Search module
SQL infoSupport of SQLnoSQL-like query languageyesno
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesJava
JavaScript
Objective-C
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Java
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 procedureslimited functionality with using 'rules'yes infoEvent Listeners, Executor ServicesyesLua
TriggersCallbacks are triggered when data changesyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesone or two-phase-commit; repeatable reads; read commitedACIDOptimistic 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 controlyes, based on authentication and database rulesRole-based access controlAccess rights for users, groups and rolessimple password-based access control and ACL

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More resources
Firebase Realtime DatabaseHazelcastInterSystems CachéKeyDB
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