DBMS > Bangdb vs. DuckDB vs. Fauna vs. NSDb vs. PostgreSQL

System Properties Comparison Bangdb vs. DuckDB vs. Fauna vs. NSDb vs. PostgreSQL

Editorial information provided by DB-Engines

Name

Description

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

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

Technical documentation

www.postgresql.org/docs

Developer

Sachin Sinha, BangDB

Fauna, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2012

2018

2014

2017

1989

1989: Postgres, 1996: PostgreSQL

Current release

BangDB 2.0, October 2021

1.0.0, June 2024

16.3, May 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

MIT License

commercial

Open Source

Apache Version 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C, C++

C++

Scala

Java, Scala

Server operating systems

Linux

server-less

hosted

Linux
macOS

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
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

yes: int, bigint, decimal, string

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like query language

yes

standard with numerous extensions

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

RESTful HTTP API

gRPC
HTTP REST
WebSocket

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

Supported programming languages

C
C#
C++
Java
Python

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Java
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

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

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

none

horizontal partitioning

consistent hashing

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

Using Apache Lucene

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)

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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