DBMS > Amazon Aurora vs. Amazon DocumentDB vs. IBM Cloudant vs. RocksDB

System Properties Comparison Amazon Aurora vs. Amazon DocumentDB vs. IBM Cloudant vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Database as a Service offering based on Apache CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Document store

Key-value store

Secondary database models

Document store

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/rds/aurora

aws.amazon.com/documentdb

www.ibm.com/products/cloudant

rocksdb.org

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

aws.amazon.com/documentdb/resources

cloud.ibm.com/docs/Cloudant

github.com/facebook/rocksdb/wiki

Developer

Amazon

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Facebook, Inc.

Initial release

2015

2019

2010

2013

Current release

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

BSD

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

C++

Server operating systems

hosted

Linux

Data scheme

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

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

Go
Java
JavaScript (Node.js)
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication
Source-replica replication

yes

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Atomic single-document operations

atomic operations within a document possible

yes

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Access rights for users can be defined per database

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