DBMS > Amazon Redshift vs. Bangdb vs. CouchDB vs. FatDB vs. Kyligence Enterprise

System Properties Comparison Amazon Redshift vs. Bangdb vs. CouchDB vs. FatDB vs. Kyligence Enterprise

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A distributed analytics engine for big data, built on top of Apache Kylin

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

Document store
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Website

aws.amazon.com/redshift

bangdb.com

couchdb.apache.org

kyligence.io/kyligence-enterprise

Technical documentation

docs.aws.amazon.com/redshift

docs.bangdb.com

docs.couchdb.org/en/stable

Developer

Amazon (based on PostgreSQL)

Sachin Sinha, BangDB

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

FatCloud

Kyligence, Inc.

Initial release

2012

2005

2012

2016

Current release

BangDB 2.0, October 2021

3.3.3, December 2023

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C, C++

Erlang

Java

Server operating systems

hosted

Linux

Android
BSD
Linux
OS X
Solaris
Windows

Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

restricted

yes

secondary, composite, nested, reverse, geospatial

yes

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL like support with command line tool

Via inetgration in SQL Server

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

RESTful HTTP/JSON API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

user defined functions

in Python

View functions in JavaScript

yes

via applications

Triggers

yes, Notifications (with Streaming only)

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

atomic operations within a single document possible

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes

yes, run db with in-memory only mode

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

Access rights for users can be defined per database

Can implement custom security layer via applications

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