DBMS > Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Atos Standard Common Repository vs. Heroic

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Atos Standard Common Repository vs. Heroic

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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

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Relational DBMS

Document store
Key-value store

Time Series DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/redshift

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

github.com/spotify/heroic

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/redshift

spotify.github.io/heroic

Developer

Alibaba

Amazon (based on PostgreSQL)

Atos Convergence Creators

Spotify

Initial release

2016

2012

2016

2014

Current release

1703

License

Commercial or Open Source

commercial

Open Source

Apache 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

Java

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

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

via Elasticsearch

SQL

Support of SQL

SQL-like query language

yes

does not fully support an SQL-standard

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

LDAP

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

Java

All languages supporting JDBC/ODBC

All languages with LDAP bindings

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

cell division

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

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

Eventual Consistency
Immediate Consistency

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

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

fine grained access rights according to SQL-standard

LDAP bind authentication

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