DBMS > Amazon Aurora vs. H2 vs. Machbase Neo vs. Snowflake

System Properties Comparison Amazon Aurora vs. H2 vs. Machbase Neo vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

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	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/rds/aurora

www.h2database.com

machbase.com

www.snowflake.com

Technical documentation

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

www.h2database.com/html/main.html

machbase.com/dbms

docs.snowflake.net/manuals/index.html

Developer

Amazon

Thomas Mueller

Machbase

Snowflake Computing Inc.

Initial release

2015

2005

2013

2014

Current release

2.2.220, July 2023

V8.0, August 2023

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free test version 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

Java

Server operating systems

hosted

All OS with a Java VM

Linux
macOS
Windows

hosted

Data scheme

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

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
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

Java

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

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

yes, multi-version concurrency control (MVCC)

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

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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

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