DBMS > Amazon DynamoDB vs. Amazon Redshift vs. BigchainDB vs. mSQL

System Properties Comparison Amazon DynamoDB vs. Amazon Redshift vs. BigchainDB vs. mSQL

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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

Large scale data warehouse service for use with business intelligence tools

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Website

aws.amazon.com/dynamodb

aws.amazon.com/redshift

www.bigchaindb.com

hughestech.com.au/products/msql

Technical documentation

docs.aws.amazon.com/dynamodb

docs.aws.amazon.com/redshift

bigchaindb.readthedocs.io/en/latest

Developer

Amazon

Amazon (based on PostgreSQL)

Hughes Technologies

Initial release

2012

2016

1994

Current release

4.4, October 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

AGPL v3

commercial

free licenses can be provided

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

Python

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

CLI Client
RESTful HTTP API

JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

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

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

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