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

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

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Distributed and scalable native Graph DBMS

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

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	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/rds/aurora

dgraph.io

hsqldb.org

www.snowflake.com

Technical documentation

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

dgraph.io/docs

hsqldb.org/web/hsqlDocsFrame.html

docs.snowflake.net/manuals/index.html

Developer

Amazon

Dgraph Labs, Inc.

Snowflake Computing Inc.

Initial release

2015

2016

2001

2014

Current release

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Java

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

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

hosted

Data scheme

yes

schema-free

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

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

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

yes

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Synchronous replication via Raft

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

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

Planned for future releases

fine grained access rights according to SQL-standard

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

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