DBMS > Amazon Neptune vs. Citus vs. CouchDB vs. Firebase Realtime Database vs. MySQL

System Properties Comparison Amazon Neptune vs. Citus vs. CouchDB vs. Firebase Realtime Database vs. MySQL

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Widely used open source RDBMS

Primary database model

Key/Value like access via memcached API

Secondary database models

Document store

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

aws.amazon.com/neptune

www.citusdata.com

couchdb.apache.org

firebase.google.com/products/realtime-database

www.mysql.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.citusdata.com

docs.couchdb.org/en/stable

firebase.google.com/docs/database

dev.mysql.com/doc

Developer

Amazon

Apache Software Foundation

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

Google

acquired by Google 2014

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2017

2010

2005

2012

1995

Current release

8.1, December 2018

3.3.3, December 2023

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

Apache version 2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Erlang

C and C++

Server operating systems

hosted

Linux

Android
BSD
Linux
OS X
Solaris
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

with proprietary extensions

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

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

RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

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

Java
JavaScript
Objective-C

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

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

View functions in JavaScript

limited functionality with using 'rules'

yes

proprietary syntax

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

improved architecture with release 2.0

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

atomic operations within a single document possible

yes

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

with encyption-at-rest

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

Access rights for users can be defined per database

yes, based on authentication and database rules

Users with fine-grained authorization concept

no user groups or roles

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