DBMS > Amazon Aurora vs. Citus vs. Google Cloud Spanner

System Properties Comparison Amazon Aurora vs. Citus vs. Google Cloud Spanner

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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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Primary database model

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store

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

Score	7.25
Rank	#46	Overall
	#29	Relational DBMS

Score	1.91
Rank	#121	Overall
	#57	Relational DBMS

Score	2.56
Rank	#97	Overall
	#50	Relational DBMS

Website

aws.amazon.com/rds/aurora

www.citusdata.com

cloud.google.com/spanner

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

docs.citusdata.com

cloud.google.com/spanner/docs

Social network pages

Developer

Amazon

Google

Initial release

2015

2010

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

8.1, December 2018

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

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

Linux

hosted

Data scheme

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes, MySQL and PostgreSQL dialects

yes

standard, with numerous extensions

yes

Query statements complying to ANSI 2011

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

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

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

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

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Full replication
Logical replication
Snapshot replication
Transactional replication

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication with 3 replicas for regional instances.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate/Strong Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID, Multi-statement

ACID

Strict serializable isolation

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

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

More information provided by the system vendor

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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

Amazon Aurora now supports R8g database instances in the AWS GovCloud (US-West) Region
2 May 2025, Amazon Web Services (AWS)

Optimizing cost savings: The advantage of Amazon Aurora over self-managed open source databases
31 March 2025, Amazon Web Services (AWS)

Introducing Amazon Aurora DSQL | Amazon Web Services
3 December 2024, Amazon Web Services (AWS)

Amazon Aurora PostgreSQL Limitless Database is now generally available
31 October 2024, Amazon Web Services (AWS)

How Heroku migrated hundreds of thousands of self-managed PostgreSQL databases to Amazon Aurora
10 April 2025, Amazon Web Services (AWS)

provided by Google News

Microsoft acquires Citus Data, re-affirming its commitment to Open Source and accelerating Azure PostgreSQL performance and scale
24 January 2019, The Official Microsoft Blog

Microsoft acquires Citus Data, creators of a cloud-friendly version of the PostgreSQL database
24 January 2019, GeekWire

Citus Data Announces Citus Cloud Database Support for HIPAA and SOC 2 Type 2 Compliance
13 November 2018, Business Wire

Microsoft acquires Citus Data
24 January 2019, TechCrunch

Microsoft acquires another open-source company, Citus Data
24 January 2019, CNBC

provided by Google News

Google Cloud Introduces HDD Tier for Spanner Database, Cutting Cold Storage Costs by 80%
22 March 2025, infoq.com

New features make Google's Spanner a database for AI
1 August 2024, TechTarget

Google Cloud Spanner gets dual-region configuration option
23 July 2024, InfoWorld

Google Cloud expands its database portfolio with new AI capabilities
1 August 2024, TechCrunch

Google Releases Spanner Graph into General Availability
19 February 2025, infoq.com

provided by Google News

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