DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Splice Machine vs. Teradata Aster

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Splice Machine vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

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

Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.alibabacloud.com/product/maxcompute

aws.amazon.com/redshift

splicemachine.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/redshift

splicemachine.com/how-it-works

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Alibaba

Amazon (based on PostgreSQL)

Splice Machine

Teradata

Initial release

2016

2012

2014

2005

Current release

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

AGPL 3.0, commercial license available

commercial

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

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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.

yes

in Aster File Store

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

SQL-like query language

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
Java
Perl
Python
R

Java

All languages supporting JDBC/ODBC

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

user defined functions

in Java

user defined functions

in Python

yes

Java

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

yes

Multi-source replication
Source-replica replication

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

yes

SQL Map-Reduce Framework

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

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

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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