DBMS > Amazon SimpleDB vs. Firebase Realtime Database vs. IBM Cloudant vs. Microsoft Azure Cosmos DB

System Properties Comparison Amazon SimpleDB vs. Firebase Realtime Database vs. IBM Cloudant vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Key-value store

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

aws.amazon.com/simpledb

firebase.google.com/products/realtime-database

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.aws.amazon.com/simpledb

firebase.google.com/docs/database

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

Developer

Amazon

Google

acquired by Google 2014

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Initial release

2007

2012

2010

2014

License

Commercial or Open Source

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

Erlang

Server operating systems

hosted

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All columns are indexed automatically

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

APIs and other access methods

RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Java
JavaScript
Objective-C

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

View functions (Map-Reduce) in JavaScript

JavaScript

Triggers

Callbacks are triggered when data changes

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrent data updates can be detected by the application

yes

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

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)

yes, based on authentication and database rules

Access rights for users can be defined per database

Access rights can be defined down to the item level

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