DBMS > Amazon Redshift vs. Amazon SimpleDB vs. Badger vs. MonetDB

System Properties Comparison Amazon Redshift vs. Amazon SimpleDB vs. Badger vs. MonetDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

A relational database management system that stores data in columns

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.89
Rank	#128	Overall
	#22	Key-value stores

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Website

aws.amazon.com/redshift

aws.amazon.com/simpledb

github.com/dgraph-io/badger

www.monetdb.org

Technical documentation

docs.aws.amazon.com/redshift

docs.aws.amazon.com/simpledb

godoc.org/github.com/dgraph-io/badger

www.monetdb.org/Documentation

Developer

Amazon (based on PostgreSQL)

Amazon

DGraph Labs

MonetDB BV

Initial release

2012

2007

2017

2004

Current release

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

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

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

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

restricted

yes

All columns are indexed automatically

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding must be implemented in the application

none

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Concurrent data updates can be detected by the application

ACID

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

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