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DBMS > Bangdb vs. Firebase Realtime Database vs. Hive vs. Splice Machine

System Properties Comparison Bangdb vs. Firebase Realtime Database vs. Hive vs. Splice Machine

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHive  Xexclude from comparisonSplice Machine  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.data warehouse software for querying and managing large distributed datasets, built on HadoopOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitebangdb.comfirebase.google.com/­products/­realtime-databasehive.apache.orgsplicemachine.com
Technical documentationdocs.bangdb.comfirebase.google.com/­docs/­databasecwiki.apache.org/­confluence/­display/­Hive/­Homesplicemachine.com/­how-it-works
DeveloperSachin Sinha, BangDBGoogle infoacquired by Google 2014Apache Software Foundation infoinitially developed by FacebookSplice Machine
Initial release2012201220122014
Current releaseBangDB 2.0, October 20213.1.3, April 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
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 systemsLinuxhostedAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes
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.nono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyes
SQL infoSupport of SQLSQL like support with command line toolnoSQL-like DML and DDL statementsyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
Python
Java
JavaScript
Objective-C
C++
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'yes infouser defined functions and integration of map-reduceyes infoJava
Triggersyes, Notifications (with Streaming only)Callbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceYes, via Full Spark Integration
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
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes, multi-version concurrency control (MVCC)
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 rights for users, groups and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
BangdbFirebase Realtime DatabaseHiveSplice Machine
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