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DBMS > Apache IoTDB vs. Bangdb vs. Firebase Realtime Database vs. Hive

System Properties Comparison Apache IoTDB vs. Bangdb vs. Firebase Realtime Database vs. Hive

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBangdb  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHive  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkConverged 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 Hadoop
Primary database modelTime Series DBMSDocument store
Graph DBMS
Time Series DBMS
Document storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
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
Websiteiotdb.apache.orgbangdb.comfirebase.google.com/­products/­realtime-databasehive.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bangdb.comfirebase.google.com/­docs/­databasecwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software FoundationSachin Sinha, BangDBGoogle infoacquired by Google 2014Apache Software Foundation infoinitially developed by Facebook
Initial release2018201220122012
Current release1.1.0, April 2023BangDB 2.0, October 20213.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxhostedAll OS with a Java VM
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyes
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 indexesyesyes infosecondary, composite, nested, reverse, geospatialyesyes
SQL infoSupport of SQLSQL-like query languageSQL like support with command line toolnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
Proprietary protocol
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
Python
Java
JavaScript
Objective-C
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyesnolimited functionality with using 'rules'yes infouser defined functions and integration of map-reduce
Triggersyesyes, Notifications (with Streaming only)Callbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor, Knob for CAP (enterprise version only)selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Tunable consistency, set CAP knob accordinglyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesno
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only mode
User concepts infoAccess controlyesyes (enterprise version only)yes, based on authentication and database rulesAccess rights for users, groups and roles

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More resources
Apache IoTDBBangdbFirebase Realtime DatabaseHive
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