DBMS > Amazon DynamoDB vs. Citus vs. Dragonfly vs. IBM Cloudant

System Properties Comparison Amazon DynamoDB vs. Citus vs. Dragonfly vs. IBM Cloudant

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Editorial information provided by DB-Engines

Name

Description

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

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Database as a Service offering based on Apache CouchDB

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store

Document store

Secondary database models

Document store

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Website

aws.amazon.com/dynamodb

www.citusdata.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.ibm.com/products/cloudant

Technical documentation

docs.aws.amazon.com/dynamodb

docs.citusdata.com

www.dragonflydb.io/docs

cloud.ibm.com/docs/Cloudant

Developer

Amazon

DragonflyDB team and community contributors

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2012

2010

2023

2010

Current release

8.1, December 2018

1.0, March 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL, commercial license also available

Open Source

BSL 1.1

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Erlang

Server operating systems

hosted

Linux

hosted

Data scheme

schema-free

yes

scheme-free

schema-free

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

SQL

Support of SQL

yes

standard, with numerous extensions

APIs and other access methods

RESTful HTTP API

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

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

user defined functions

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

Lua

View functions (Map-Reduce) in JavaScript

Triggers

yes

by integration with AWS Lambda

yes

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

Multi-source replication
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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

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

ACID

Atomic execution of command blocks and scripts

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Optimistic locking

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.

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

Password-based authentication

Access rights for users can be defined per database

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