DBMS > Amazon DynamoDB vs. Memcached vs. Microsoft Azure Table Storage

System Properties Comparison Amazon DynamoDB vs. Memcached vs. Microsoft Azure Table Storage

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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

In-memory key-value store, originally intended for caching

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Document store
Key-value store

Key-value store

Wide column 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	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Website

aws.amazon.com/dynamodb

www.memcached.org

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/memcached/memcached/wiki

Developer

Amazon

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Initial release

2012

2003

2012

Current release

1.6.25, March 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD license

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

hosted

FreeBSD
Linux
OS X
Unix
Windows

hosted

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

Proprietary protocol

RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Repcached, a Memcached patch, provides this functionallity

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate 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

optimistic locking

Concurrency

Support for concurrent manipulation of data

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

using SASL (Simple Authentication and Security Layer) protocol

Access rights based on private key authentication or shared access signatures

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