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DBMS > Bangdb vs. Firebase Realtime Database vs. HBase vs. Hive

System Properties Comparison Bangdb vs. Firebase Realtime Database vs. HBase vs. Hive

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphCloud-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 BigTabledata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document storeWide column storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websitebangdb.comfirebase.google.com/­products/­realtime-databasehbase.apache.orghive.apache.org
Technical documentationdocs.bangdb.comfirebase.google.com/­docs/­databasehbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperSachin Sinha, BangDBGoogle infoacquired by Google 2014Apache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by Facebook
Initial release2012201220082012
Current releaseBangDB 2.0, October 20212.3.4, January 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaJava
Server operating systemsLinuxhostedLinux
Unix
Windows infousing Cygwin
All OS with a Java VM
Data schemeschema-freeschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesoptions to bring your own types, AVROyes
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 indexesyes infosecondary, composite, nested, reverse, geospatialyesnoyes
SQL infoSupport of SQLSQL like support with command line toolnonoSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Supported programming languagesC
C#
C++
Java
Python
Java
JavaScript
Objective-C
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'yes infoCoprocessors in Javayes infouser defined functions and integration of map-reduce
Triggersyes, Notifications (with Streaming only)Callbacks are triggered when data changesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication
Source-replica replication
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyes
User concepts infoAccess controlyes (enterprise version only)yes, based on authentication and database rulesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles

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BangdbFirebase Realtime DatabaseHBaseHive
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