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DBMS > Bangdb vs. Databricks vs. Sequoiadb

System Properties Comparison Bangdb vs. Databricks vs. Sequoiadb

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDatabricks  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.NewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document store
Relational DBMS
Document store
Relational DBMS
Secondary database modelsSpatial 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
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score0.48
Rank#260  Overall
#41  Document stores
#121  Relational DBMS
Websitebangdb.comwww.databricks.comwww.sequoiadb.com
Technical documentationdocs.bangdb.comdocs.databricks.comwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperSachin Sinha, BangDBDatabricksSequoiadb Ltd.
Initial release201220132013
Current releaseBangDB 2.0, October 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++
Server operating systemsLinuxhostedLinux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes infooid, date, timestamp, binary, regex
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, geospatialyesyes
SQL infoSupport of SQLSQL like support with command line toolwith Databricks SQLSQL-like query language
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
proprietary protocol using JSON
Supported programming languagesC
C#
C++
Java
Python
Python
R
Scala
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesJavaScript
Triggersyes, Notifications (with Streaming only)no
Partitioning methods infoMethods for storing different data on different nodesSharding (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 factor, Knob for CAP (enterprise version only)yesSource-replica replication
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDDocument is locked during a transaction
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 modenono
User concepts infoAccess controlyes (enterprise version only)simple password-based access control
More information provided by the system vendor
BangdbDatabricksSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BangdbDatabricksSequoiadb
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