DBMS > Alibaba Cloud MaxCompute vs. Cubrid vs. Databend vs. Spark SQL

System Properties Comparison Alibaba Cloud MaxCompute vs. Cubrid vs. Databend vs. Spark SQL

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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

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

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Spark SQL is a component on top of 'Spark Core' for structured data processing

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	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

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

github.com/datafuselabs/databend
www.databend.com

spark.apache.org/sql

Technical documentation

www.alibabacloud.com/help/en/maxcompute

cubrid.org/manuals

docs.databend.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Alibaba

CUBRID Corporation, CUBRID Foundation

Databend Labs

Apache Software Foundation

Initial release

2016

2008

2021

2014

Current release

11.0, January 2021

1.0.59, April 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Rust

Scala

Server operating systems

hosted

Linux
Windows

hosted
Linux
macOS

Linux
OS X
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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
JDBC
ODBC
OLE DB

CLI Client
JDBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

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

Go
Java
JavaScript (Node.js)
Python
Rust

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

in Java

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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.

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles

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