DBMS > Amazon Redshift vs. Atos Standard Common Repository vs. BigchainDB vs. MariaDB vs. SWC-DB

System Properties Comparison Amazon Redshift vs. Atos Standard Common Repository vs. BigchainDB vs. MariaDB vs. SWC-DB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Document store
Key-value store

Document store

Relational DBMS

Wide column store

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

aws.amazon.com/redshift

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.bigchaindb.com

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.aws.amazon.com/redshift

bigchaindb.readthedocs.io/en/latest

mariadb.com/kb/en/library

Developer

Amazon (based on PostgreSQL)

Atos Convergence Creators

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Alex Kashirin

Initial release

2012

2016

2009

Fork of MySQL, which was first released in 1995

2020

Current release

1703

11.3.2, February 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

GPL V3

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

Java

Python

C and C++

C++

Server operating systems

hosted

Linux

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

Dynamic columns are supported

schema-free

Typing

predefined data types such as float or date

yes

optional

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC

LDAP

CLI Client
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

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

C++

Server-side scripts

Stored procedures

user defined functions

in Python

yes

PL/SQL compatibility added with version 10.3

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

several options for horizontal partitioning and Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

not for in-memory storage engine

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

with MEMORY storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

LDAP bind authentication

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
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Key customers

Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
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Market metrics

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Licensing and pricing models

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