DBMS > Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Hazelcast vs. Kinetica vs. MonetDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Hazelcast vs. Kinetica vs. MonetDB

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

Large scale data warehouse service for use with business intelligence tools

A widely adopted in-memory data grid

Fully vectorized database across both GPUs and CPUs

A relational database management system that stores data in columns

Primary database model

Relational DBMS

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

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/redshift

hazelcast.com

www.kinetica.com

www.monetdb.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/redshift

hazelcast.org/imdg/docs

docs.kinetica.com

www.monetdb.org/Documentation

Developer

Alibaba

Amazon (based on PostgreSQL)

Hazelcast

Kinetica

MonetDB BV

Initial release

2016

2012

2008

2012

2004

Current release

5.3.6, November 2023

7.1, August 2021

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Mozilla Public License 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

C, C++

Server operating systems

hosted

All OS with a Java VM

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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

the object must implement a serialization strategy

Secondary indexes

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

does not fully support an SQL-standard

SQL-like query language

SQL-like DML and DDL statements

yes

SQL 2003 with some extensions

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

Java

All languages supporting JDBC/ODBC

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C++
Java
JavaScript (Node.js)
Python

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in Python

yes

Event Listeners, Executor Services

user defined functions

yes, in SQL, C, R

Triggers

yes

Events

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Replicated Map

Source-replica replication

none

Source-replica replication available in experimental status

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 selectable by user

Raft Consensus Algorithm

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

one or two-phase-commit; repeatable reads; read commited

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

GPU vRAM or System RAM

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Role-based access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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