DBMS > Amazon Redshift vs. Apache Kylin vs. Atos Standard Common Repository vs. BigchainDB

System Properties Comparison Amazon Redshift vs. Apache Kylin vs. Atos Standard Common Repository vs. BigchainDB

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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

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

Primary database model

Relational DBMS

Document store
Key-value store

Document store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Website

aws.amazon.com/redshift

kylin.apache.org

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

www.bigchaindb.com

Technical documentation

docs.aws.amazon.com/redshift

kylin.apache.org/docs

bigchaindb.readthedocs.io/en/latest

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation, originally contributed from eBay Inc

Atos Convergence Creators

Initial release

2012

2015

2016

Current release

3.1.0, July 2020

1703

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

AGPL v3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Python

Server operating systems

hosted

Linux

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

yes

optional

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

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

LDAP

CLI Client
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

LDAP bind authentication

yes

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