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

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

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

A widely adopted in-memory data grid

Fully vectorized database across both GPUs and CPUs

Primary database model

Relational DBMS

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

Relational DBMS

Relational DBMS
Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS
Time Series DBMS

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

Score	0.78
Rank	#221	Overall
	#102	Relational DBMS

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.73
Rank	#227	Overall
	#104	Relational DBMS
	#18	Time Series DBMS

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/redshift

www.mcobject.com

hazelcast.com

www.kinetica.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/redshift

www.mcobject.com/docs/extremedb.htm

hazelcast.org/imdg/docs

docs.kinetica.com

Developer

Alibaba

Amazon (based on PostgreSQL)

McObject

Hazelcast

Kinetica

Initial release

2016

2012

2001

2008

2012

Current release

8.2, 2021

5.3.6, November 2023

7.1, August 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

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 and C++

Java

C, C++

Server operating systems

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux

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.

support of XML interfaces available

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

yes

with the option: eXtremeSQL

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

All languages supporting JDBC/ODBC

.Net
C
C#
C++
Java
Lua
Python
Scala

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

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in Python

yes

Event Listeners, Executor Services

user defined functions

Triggers

yes

by defining events

yes

Events

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning / sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

Replicated Map

Source-replica replication

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

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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