DBMS > Amazon DynamoDB vs. CouchDB vs. FatDB vs. Kyligence Enterprise vs. Sequoiadb

System Properties Comparison Amazon DynamoDB vs. CouchDB vs. FatDB vs. Kyligence Enterprise vs. Sequoiadb

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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

NewSQL database with distributed OLTP and SQL

Primary database model

Document store
Key-value store

Document store

Document store
Key-value store

Relational DBMS

Document 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	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

aws.amazon.com/dynamodb

couchdb.apache.org

kyligence.io/kyligence-enterprise

www.sequoiadb.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.couchdb.org/en/stable

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Amazon

Apache Software Foundation

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

FatCloud

Kyligence, Inc.

Sequoiadb Ltd.

Initial release

2012

2005

2012

2016

2013

Current release

3.3.3, December 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache version 2

commercial

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Java

C++

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

yes

via views

yes

SQL

Support of SQL

Via inetgration in SQL Server

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

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

JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

via applications

JavaScript

Triggers

yes

by integration with AWS Lambda

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

atomic operations within a single document possible

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users can be defined per database

Can implement custom security layer via applications

simple password-based access control

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