DBMS > Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Datomic vs. GridGain vs. MySQL

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Datomic vs. GridGain vs. MySQL

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

GridGain is an in-memory computing platform, built on Apache Ignite

Widely used open source RDBMS

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

Relational DBMS

Key/Value like access via memcached API

Secondary database models

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/redshift

www.datomic.com

www.gridgain.com

www.mysql.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/redshift

docs.datomic.com

www.gridgain.com/docs/index.html

dev.mysql.com/doc

Developer

Alibaba

Amazon (based on PostgreSQL)

Cognitect

GridGain Systems, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2012

2007

1995

Current release

1.0.6735, June 2023

GridGain 8.5.1

8.4.0, April 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java, Clojure

Java, C++, .Net

C and C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

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

Secondary indexes

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

does not fully support an SQL-standard

ANSI-99 for query and DML statements, subset of DDL

yes

with proprietary extensions

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

All languages supporting JDBC/ODBC

Clojure
Java

C#
C++
Java
PHP
Python
Ruby
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in Python

yes

Transaction Functions

yes (compute grid and cache interceptors can be used instead)

yes

proprietary syntax

Triggers

By using transaction functions

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

But extensive use of caching in the application peers

yes (replicated cache)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

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

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

Users with fine-grained authorization concept

no user groups or roles

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