DBMS > Alibaba Cloud MaxCompute vs. Altibase vs. Amazon Redshift vs. openGauss vs. TimescaleDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Altibase vs. Amazon Redshift vs. openGauss vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

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

An enterprise grade, high-performance RDBMS

Large scale data warehouse service for use with business intelligence tools

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

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

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.alibabacloud.com/product/maxcompute

altibase.com

aws.amazon.com/redshift

gitee.com/opengauss
opengauss.org

www.timescale.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.aws.amazon.com/redshift

docs.opengauss.org/en
gitee.com/opengauss/docs

docs.timescale.com

Developer

Alibaba

Altibase

Amazon (based on PostgreSQL)

Huawei and openGauss community

Timescale

Initial release

2016

1999

2012

2019

2017

Current release

v7.3, 2023, August 2023

3.0, March 2022

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

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

C++

C, C++, Java

Server operating systems

hosted

AIX
HP-UX
Linux

hosted

Linux

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

restricted

yes

SQL

Support of SQL

SQL-like query language

ANSI SQL-92

yes

does not fully support an SQL-standard

ANSI SQL 2011

yes

full PostgreSQL SQL syntax

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

C
C++
Java

All languages supporting JDBC/ODBC

C
C++
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Java

stored procedures and stored functions

user defined functions

in Python

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning (by range, list and hash)

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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