DBMS > Amazon Aurora vs. gStore vs. HyperSQL vs. Snowflake

System Properties Comparison Amazon Aurora vs. gStore vs. HyperSQL vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

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

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/rds/aurora

en.gstore.cn

hsqldb.org

www.snowflake.com

Technical documentation

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

en.gstore.cn/#/enDocs

hsqldb.org/web/hsqlDocsFrame.html

docs.snowflake.net/manuals/index.html

Developer

Amazon

Snowflake Computing Inc.

Initial release

2015

2016

2001

2014

Current release

1.2, November 2023

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

based on BSD license

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

C++

Java

Server operating systems

hosted

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

Data scheme

yes

schema-free and OWL/RDFS-schema support

yes

support of semi-structured data formats (JSON, XML, Avro)

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

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API
SPARQL 1.1

HTTP API

JDBC via HTTP
JDBC
ODBC

CLI Client
JDBC
ODBC

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

C++
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC
Java

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Java, SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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