DBMS > AgensGraph vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. Spark SQL

System Properties Comparison AgensGraph vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon Redshift vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Large scale data warehouse service for use with business intelligence tools

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

bitnine.net/agensgraph

www.alibabacloud.com/product/hybriddb-postgresql

aws.amazon.com/redshift

spark.apache.org/sql

Technical documentation

bitnine.net/documentation

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

docs.aws.amazon.com/redshift

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

Developer

Bitnine Global Inc.

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Amazon (based on PostgreSQL)

Apache Software Foundation

Initial release

2016

2012

2014

Current release

2.1, December 2018

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

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

Scala

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

depending on used data model

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

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Implicit feature of the cloud service

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

fine grained access rights according to SQL-standard

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