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

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

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonBrytlyt  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSDocument 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
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.combrytlyt.iofirebase.google.com/­products/­realtime-databasespark.apache.org/­sql
Technical documentationdocs.bangdb.comdocs.brytlyt.iofirebase.google.com/­docs/­databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBBrytlytGoogle infoacquired by Google 2014Apache Software Foundation
Initial release2012201620122014
Current releaseBangDB 2.0, October 20215.0, August 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C, C++ and CUDAScala
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesno
SQL infoSupport of SQLSQL like support with command line toolyesnoSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Java
JavaScript
Objective-C
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLlimited functionality with using 'rules'no
Triggersyes, Notifications (with Streaming only)yesCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesno
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)fine grained access rights according to SQL-standardyes, based on authentication and database rulesno

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More resources
BangdbBrytlytFirebase Realtime DatabaseSpark SQL
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