DBMS > Amazon Aurora vs. Google Cloud Spanner vs. gStore vs. MySQL vs. Warp 10

System Properties Comparison Amazon Aurora vs. Google Cloud Spanner vs. gStore vs. MySQL vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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.

A native Graph DBMS to store and maintain very large RDF datasets.

Widely used open source RDBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/rds/aurora

cloud.google.com/spanner

en.gstore.cn

www.mysql.com

www.warp10.io

Technical documentation

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

cloud.google.com/spanner/docs

en.gstore.cn/#/enDocs

dev.mysql.com/doc

www.warp10.io/content/02_Getting_started

Developer

Amazon

Google

Oracle

since 2010, originally MySQL AB, then Sun

SenX

Initial release

2015

2017

2016

1995

2015

Current release

1.2, November 2023

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache License 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C++

C and C++

Java

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

Query statements complying to ANSI 2011

yes

with proprietary extensions

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

HTTP API
SPARQL 1.1

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Jupyter
WebSocket

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++
Java
JavaScript (Node.js)
PHP
Python

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

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

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

based on HBase

Foreign keys

Referential integrity

yes

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

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Strict serializable isolation

yes

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

Users with fine-grained authorization concept

no user groups or roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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