DBMS > Bangdb vs. Citus vs. openGemini vs. PouchDB

System Properties Comparison Bangdb vs. Citus vs. openGemini vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Spatial DBMS

Document store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

bangdb.com

www.citusdata.com

www.opengemini.org
github.com/openGemini

pouchdb.com

Technical documentation

docs.bangdb.com

docs.citusdata.com

docs.opengemini.org/guide

pouchdb.com/guides

Developer

Sachin Sinha, BangDB

Huawei and openGemini community

Apache Software Foundation

Initial release

2012

2010

2022

2012

Current release

BangDB 2.0, October 2021

8.1, December 2018

1.1, July 2023

7.1.1, June 2019

License

Commercial or Open Source

Open Source

BSD 3

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

JavaScript

Server operating systems

Linux

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

Integer, Float, Boolean, String

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

via views

SQL

Support of SQL

SQL like support with command line tool

yes

standard, with numerous extensions

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

JavaScript

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

View functions in JavaScript

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

other methods possible by using 3rd party extensions

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Administrators and common users accounts

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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