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DBMS > Bangdb vs. Microsoft Azure SQL Database vs. Spark SQL

System Properties Comparison Bangdb vs. Microsoft Azure SQL Database vs. Spark SQL

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.15
Rank#334  Overall
#45  Document stores
#31  Graph DBMS
#31  Time Series DBMS
Score78.40
Rank#15  Overall
#10  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sql
Technical documentationdocs.bangdb.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBMicrosoftApache Software Foundation
Initial release201220102014
Current releaseBangDB 2.0, October 2021V123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++Scala
Server operating systemsLinuxhostedLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: 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.noyesno
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesno
SQL infoSupport of SQLSQL like support with command line toolyesSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoTransact SQLno
Triggersyes, Notifications (with Streaming only)yesno
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)yes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyes, 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.yes, run db with in-memory only modeno
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardno

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More resources
BangdbMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQL
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