DBMS > Alibaba Cloud MaxCompute vs. Apache Kylin vs. Spark SQL vs. Transwarp ArgoDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Apache Kylin vs. Spark SQL vs. Transwarp ArgoDB

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Name

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Relational DBMS

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

Relational DBMS

Secondary database models

Search engine

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

kylin.apache.org

spark.apache.org/sql

www.transwarp.cn/en/product/argodb

Technical documentation

www.alibabacloud.com/help/en/maxcompute

kylin.apache.org/docs

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

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Alibaba

Apache Software Foundation, originally contributed from eBay Inc

Apache Software Foundation

Transwarp

Initial release

2016

2015

2014

Current release

3.1.0, July 2020

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Java

Scala

Server operating systems

hosted

Linux

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

ANSI SQL for queries (using Apache Calcite)

SQL-like DML and DDL statements

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

in Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

Transaction concepts

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

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

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