DBMS > Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Hive vs. Pinecone

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon Redshift vs. Hive vs. Pinecone

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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

Large scale data warehouse service for use with business intelligence tools

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A managed, cloud-native vector database

Primary database model

Relational DBMS

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

Relational DBMS

Vector 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	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/redshift

hive.apache.org

www.pinecone.io

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/redshift

cwiki.apache.org/confluence/display/Hive/Home

docs.pinecone.io/docs/overview

Developer

Alibaba

Amazon (based on PostgreSQL)

Apache Software Foundation

initially developed by Facebook

Pinecone Systems, Inc

Initial release

2016

2012

2019

Current release

3.1.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

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

Server operating systems

hosted

All OS with a Java VM

hosted

Data scheme

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

restricted

yes

SQL

Support of SQL

SQL-like query language

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC

JDBC
ODBC
Thrift

RESTful HTTP API

Supported programming languages

Java

All languages supporting JDBC/ODBC

C++
Java
PHP
Python

Python

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in Python

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

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.

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

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