DBMS > Amazon Aurora vs. Amazon Neptune

System Properties Comparison Amazon Aurora vs. Amazon Neptune

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Our visitors often compare Amazon Aurora and Amazon Neptune with Microsoft Azure Cosmos DB, Amazon DynamoDB and OpenSearch.

Editorial information provided by DB-Engines

Name

Description

Fully managed relational database service built for the cloud providing unparalleled high performance and availability at global scale for MySQL, PostgreSQL, and DSQL

Fast, reliable graph database built for the cloud

Primary database model

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	7.99
Rank	#44	Overall
	#28	Relational DBMS

Score	2.07
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Website

aws.amazon.com/rds/aurora

aws.amazon.com/neptune

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_AuroraOverview.html
docs.aws.amazon.com/aurora-dsql/latest/userguide/what-is-aurora-dsql.html

aws.amazon.com/neptune/developer-resources

Social network pages

Developer

Amazon

Initial release

2015

2017

Current release

Aurora DSQL, November 2024 (preview), PostgreSQL: docs.aws.amazon.com/AmazonRDS/latest/AuroraPostgreSQLReleaseNotes/AuroraPostgreSQL.Updates.html , MySQL: docs.aws.amazon.com/AmazonRDS/latest/AuroraMySQLReleaseNotes/AuroraMySQL.release-calendars.html

License

Commercial or Open Source

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

PostgreSQL/MySQL: C, C++, Aurora DSQL: Rust

Server operating systems

Amazon Linux

hosted

Data scheme

yes

schema-free

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

SQL

Support of SQL

yes, MySQL and PostgreSQL dialects

APIs and other access methods

DSQL API: docs.aws.amazon.com/aurora-dsql/latest/userguide/CHAP_api_reference.html
MySQL wire protocol
PostgreSQL wire protocol
RDS Data API: docs.aws.amazon.com/AmazonRDS/latest/UserGuide/ProgrammingGuide.html

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Rust
Scheme
Tcl

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

PL/pgSQL, MySQL stored program language, APG trusted language extensions

Triggers

Aurora MySQL: Yes. Aurora PostgreSQL: Yes. Aurora DSQL: No.

Partitioning methods

Methods for storing different data on different nodes

DBMS table partitioning, Horizontal storage partitioning, Sharding, Distributed horizontal partitioning (DSQL)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Full replication
Logical replication
Snapshot replication
Transactional replication

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate/Strong Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID, Multi-statement

ACID

Concurrency

Support for concurrent manipulation of data

Multiversion concurrency control (MVCC) with fully compatible MySQL and PostgreSQL options. Optimistic concurrency control (OCC) in Aurora DSQL.

yes

Durability

Support for making data persistent

Data is replicated across 3 Availability Zones (AZs) within a single AWS Region. Active-active multi-Region high availability across 3 Regions (2 active, 1 witness) and automated failover recovery with Aurora DSQL. Automated, continuous backup of data with point in time restore. Fault-tolerant, self-healing storage system.

yes

with encyption-at-rest

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Role based permissions
Row level security

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

More information provided by the system vendor

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Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

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Recent citations in the news

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14 March 2025, AWS Blog

Upgrade strategies for Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL 12
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31 October 2024, AWS Blog

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