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DBMS > Firebase Realtime Database vs. HBase vs. KeyDB vs. Spark SQL

System Properties Comparison Firebase Realtime Database vs. HBase vs. KeyDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonHBase  Xexclude from comparisonKeyDB  Xexclude from comparisonSpark SQL  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.Wide-column store based on Apache Hadoop and on concepts of BigTableAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeWide column storeKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasehbase.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
spark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­databasehbase.apache.org/­book.htmldocs.keydb.devspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogle infoacquired by Google 2014Apache Software Foundation infoApache top-level project, originally developed by PowersetEQ Alpha Technology Ltd.Apache Software Foundation
Initial release2012200820192014
Current release2.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoBSD-3Open Source infoApache 2.0
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++Scala
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
LinuxLinux
OS X
Windows
Data schemeschema-freeschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROpartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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 indexesyesnoyes infoby using the Redis Search moduleno
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
Proprietary protocol infoRESP - REdis Serialization ProtocoJDBC
ODBC
Supported programming languagesJava
JavaScript
Objective-C
C
C#
C++
Groovy
Java
PHP
Python
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
Java
Python
R
Scala
Server-side scripts infoStored procedureslimited functionality with using 'rules'yes infoCoprocessors in JavaLuano
TriggersCallbacks are triggered when data changesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
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 ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesSingle row ACID (across millions of columns)Optimistic locking, atomic execution of commands blocks and scriptsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyes, based on authentication and database rulesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control and ACLno

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More resources
Firebase Realtime DatabaseHBaseKeyDBSpark SQL
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