DBMS > Amazon Aurora vs. FatDB vs. Hypertable vs. Snowflake

System Properties Comparison Amazon Aurora vs. FatDB vs. Hypertable vs. Snowflake

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

MySQL and PostgreSQL compatible cloud service by Amazon

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Primary database model

Relational DBMS

Document store
Key-value store

Wide column 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	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/rds/aurora

www.snowflake.com

Technical documentation

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

docs.snowflake.net/manuals/index.html

Developer

Amazon

FatCloud

Hypertable Inc.

Snowflake Computing Inc.

Initial release

2015

2012

2009

2014

Current release

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license 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

C++

Server operating systems

hosted

Windows

Linux
OS X
Windows

an inofficial Windows port is available

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

Via inetgration in SQL Server

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

C++ API
Thrift

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
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

user defined functions

Triggers

yes

via applications

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

selectable replication factor on file system level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

Can implement custom security layer via applications

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

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