DBMS > Amazon Aurora vs. atoti vs. Google Cloud Spanner vs. YugabyteDB

System Properties Comparison Amazon Aurora vs. atoti vs. Google Cloud Spanner vs. YugabyteDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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.

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Relational DBMS

Object oriented DBMS

Relational DBMS

Secondary database models

Document store

Document store
Wide column store

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

Score	7.84
Rank	#44	Overall
	#28	Relational DBMS

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	2.48
Rank	#108	Overall
	#53	Relational DBMS

Website

aws.amazon.com/rds/aurora

atoti.io

cloud.google.com/spanner

www.yugabyte.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.atoti.io

cloud.google.com/spanner/docs

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Amazon

ActiveViam

Google

Yugabyte Inc.

Initial release

2015

2017

Current release

2.19, September 2023

License

Commercial or Open Source

commercial

free versions available

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.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

Java

C and C++

Server operating systems

hosted

Linux
OS X

Data scheme

yes

depending on used data model

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

Multidimensional Expressions (MDX)

yes

Query statements complying to ANSI 2011

yes, PostgreSQL compatible

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC (using protocol buffers) API
JDBC

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

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

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

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

Python

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding, horizontal partitioning

Sharding

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

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

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

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

yes

Transaction concepts

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

ACID

Strict serializable isolation

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

based on RocksDB

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

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

yes

More information provided by the system vendor

Specific characteristics

YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more

Competitive advantages

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more

Typical application scenarios

Systems of record and engagement for cloud native applications that require resilience,...
» more

Market metrics

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more

Licensing and pricing models

Apache 2.0 license for the database
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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

show all

Recent citations in the news

Migrate SQL Server databases to Babelfish for Aurora PostgreSQL using change tracking with a linked server
24 September 2024, AWS Blog

Replace Amazon QLDB with Amazon Aurora PostgreSQL for audit use cases
18 July 2024, AWS Blog

Review your Amazon Aurora and Amazon RDS security configuration with Prowler’s new checks
6 August 2024, AWS Blog

Build generative AI applications with Amazon Aurora and Amazon Bedrock Knowledge Bases
2 February 2024, AWS Blog

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda
14 May 2024, AWS Blog

provided by Google News

ActiveViam Announces Leadership Succession
4 September 2024, Business Wire

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

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

Google Cloud adds graph and vector search features to Spanner database
2 August 2024, Techzine Europe

Google Cloud Enhances Spanner with Dual-Region Configuration
1 August 2024, InfoQ.com

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

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

provided by Google News

YugabyteDB Evolves PostgreSQL to a Distributed Architecture for Modern, Cloud-Native Applications
19 September 2024, Business Wire

YugabyteDB evolves into a distributed PostgreSQL database for apps that need resilience and scale
19 September 2024, SiliconANGLE News

YugabyteDB 2.19 gets new PostgreSQL-compatibility features
19 September 2024, InfoWorld

YugabyteDB Becomes First Distributed SQL Database Vendor to Complete CIS Benchmark
1 February 2024, Datanami

Simplifying cloud-native app development with Yugabyte
2 August 2024, IMDA

provided by Google News

Share this page