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DBMS > Bangdb vs. Citus vs. Immudb vs. Spark SQL

System Properties Comparison Bangdb vs. Citus vs. Immudb vs. Spark SQL

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonCitus  Xexclude from comparisonImmudb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMSDocument storeRelational 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
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.24
Rank#305  Overall
#43  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitebangdb.comwww.citusdata.comgithub.com/­codenotary/­immudb
immudb.io
spark.apache.org/­sql
Technical documentationdocs.bangdb.comdocs.citusdata.comdocs.immudb.iospark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBCodenotaryApache Software Foundation
Initial release2012201020202014
Current releaseBangDB 2.0, October 20218.1, December 20181.2.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoAGPL, commercial license also availableOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++CGoScala
Server operating systemsLinuxLinuxBSD
Linux
macOS
Solaris
Windows
z/OS
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyes
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.noyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesno
SQL infoSupport of SQLSQL like support with command line toolyes infostandard, with numerous extensionsSQL-like syntaxSQL-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
gRPC protocol
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersyes, Notifications (with Streaming only)yesnono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Source-replica replication infoother methods possible by using 3rd party extensionsnone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
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 modenonono
User concepts infoAccess controlyes (enterprise version only)fine grained access rights according to SQL-standardno

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More resources
BangdbCitusImmudbSpark SQL
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