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DBMS > Bangdb vs. Spark SQL vs. TimescaleDB

System Properties Comparison Bangdb vs. Spark SQL vs. TimescaleDB

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphSpark SQL is a component on top of 'Spark Core' for structured data processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMSRelational 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitebangdb.comspark.apache.org/­sqlwww.timescale.com
Technical documentationdocs.bangdb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperSachin Sinha, BangDBApache Software FoundationTimescale
Initial release201220142017
Current releaseBangDB 2.0, October 20213.5.0 ( 2.13), September 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ScalaC
Server operating systemsLinuxLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialnoyes
SQL infoSupport of SQLSQL like support with command line toolSQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Java
Python
Java
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes, Notifications (with Streaming only)noyes
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 Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)noneSource-replica replication with hot standby and reads on replicas info
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 integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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)nofine grained access rights according to SQL-standard

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More resources
BangdbSpark SQLTimescaleDB
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