DBMS > Alibaba Cloud MaxCompute vs. Apache IoTDB vs. Cubrid vs. Microsoft Azure AI Search vs. MySQL

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache IoTDB vs. Cubrid vs. Microsoft Azure AI Search 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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Search-as-a-service for web and mobile app development

Widely used open source RDBMS

Primary database model

Relational DBMS

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

Key/Value like access via memcached API

Secondary database models

Vector 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	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

iotdb.apache.org

cubrid.com (korean)
cubrid.org (english)

azure.microsoft.com/en-us/services/search

www.mysql.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

cubrid.org/manuals

learn.microsoft.com/en-us/azure/search

dev.mysql.com/doc

Developer

Alibaba

Apache Software Foundation

CUBRID Corporation, CUBRID Foundation

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2018

2008

2015

1995

Current release

1.1.0, April 2023

11.0, January 2021

8.3.0, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C, C++, Java

C and C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux
Windows

hosted

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

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
Native API

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

C
C#
C++
Go
Java
Python
Scala

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

C#
Java
JavaScript
Python

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

yes

Java Stored Procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Sharding

Implicit feature of the cloud service

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

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

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

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

yes

fine grained access rights according to SQL-standard

yes

using Azure authentication

Users with fine-grained authorization concept

no user groups or roles

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