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DBMS > Bangdb vs. Firebase Realtime Database vs. Hypertable vs. Spark SQL

System Properties Comparison Bangdb vs. Firebase Realtime Database vs. Hypertable vs. Spark SQL

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHypertable  Xexclude from comparisonSpark SQL  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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.An open source BigTable implementation based on distributed file systems such as HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
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
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.comfirebase.google.com/­products/­realtime-databasespark.apache.org/­sql
Technical documentationdocs.bangdb.comfirebase.google.com/­docs/­databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBGoogle infoacquired by Google 2014Hypertable Inc.Apache Software Foundation
Initial release2012201220092014
Current releaseBangDB 2.0, October 20210.9.8.11, March 20163.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++Scala
Server operating systemsLinuxhostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesnoyes
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, geospatialyesrestricted infoonly exact value or prefix value scansno
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
C++ API
Thrift
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
Java
JavaScript
Objective-C
C++
Java
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'nono
Triggersyes, Notifications (with Streaming only)Callbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)selectable replication factor on file system levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
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
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnono
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 modeno
User concepts infoAccess controlyes (enterprise version only)yes, based on authentication and database rulesnono

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More resources
BangdbFirebase Realtime DatabaseHypertableSpark SQL
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