DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Alibaba Cloud MaxCompute vs. EJDB vs. Spark SQL

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Alibaba Cloud MaxCompute vs. EJDB vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Document store

Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.alibabacloud.com/product/maxcompute

github.com/Softmotions/ejdb

spark.apache.org/sql

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

www.alibabacloud.com/help/en/maxcompute

github.com/Softmotions/ejdb/blob/master/README.md

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

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Alibaba

Softmotions

Apache Software Foundation

Initial release

2016

2012

2014

Current release

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

Apache 2.0

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

Scala

Server operating systems

hosted

server-less

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

yes

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

Fluentd
Flume
MaxCompute Console

in-process shared library

JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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

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

yes

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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