DBMS > Bangdb vs. Postgres-XL vs. PouchDB vs. Transbase

System Properties Comparison Bangdb vs. Postgres-XL vs. PouchDB vs. Transbase

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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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

JavaScript DBMS with an API inspired by CouchDB

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

bangdb.com

www.postgres-xl.org

pouchdb.com

www.transaction.de/en/products/transbase.html

Technical documentation

docs.bangdb.com

www.postgres-xl.org/documentation

pouchdb.com/guides

www.transaction.de/en/products/transbase/features.html

Developer

Sachin Sinha, BangDB

Apache Software Foundation

Transaction Software GmbH

Initial release

2012

2014

since 2012, originally named StormDB

2012

1987

Current release

BangDB 2.0, October 2021

10 R1, October 2018

7.1.1, June 2019

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Mozilla public license

Open Source

commercial

free development license

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C, C++

JavaScript

C and C++

Server operating systems

Linux

Linux
macOS

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

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

via views

yes

SQL

Support of SQL

SQL like support with command line tool

yes

distributed, parallel query execution

yes

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Java
Python

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

JavaScript

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

yes

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

horizontal partitioning

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)

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

yes

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

yes

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

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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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