DBMS > AgensGraph vs. Alibaba Cloud MaxCompute vs. Amazon DocumentDB vs. Spark SQL

System Properties Comparison AgensGraph vs. Alibaba Cloud MaxCompute vs. Amazon DocumentDB 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

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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

Primary database model

Graph DBMS
Relational DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

bitnine.net/agensgraph

www.alibabacloud.com/product/maxcompute

aws.amazon.com/documentdb

spark.apache.org/sql

Technical documentation

bitnine.net/documentation

www.alibabacloud.com/help/en/maxcompute

aws.amazon.com/documentdb/resources

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

Developer

Bitnine Global Inc.

Alibaba

Apache Software Foundation

Initial release

2016

2019

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

depending on used data model

yes

schema-free

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

yes

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

Cypher Query Language
JDBC

Fluentd
Flume
MaxCompute Console

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

Java

Go
Java
JavaScript (Node.js)
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

in Java

Triggers

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

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Atomic single-document operations

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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