DBMS > Amazon Aurora vs. Riak KV vs. Snowflake vs. VoltDB

System Properties Comparison Amazon Aurora vs. Riak KV vs. Snowflake vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Distributed, fault tolerant key-value store

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store

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

Score	8.50
Rank	#49	Overall
	#31	Relational DBMS

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

aws.amazon.com/rds/aurora

www.snowflake.com

www.voltdb.com

Technical documentation

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

www.tiot.jp/riak-docs/riak/kv/latest

docs.snowflake.net/manuals/index.html

docs.voltdb.com

Developer

Amazon

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

VoltDB Inc.

Initial release

2015

2009

2014

2010

Current release

3.2.0, December 2022

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Java, C++

Server operating systems

hosted

Linux
OS X

hosted

Linux
OS X

for development

Data scheme

yes

schema-free

yes

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

yes

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

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Erlang

user defined functions

Java

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

no "single point of failure"

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

yes

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

yes, using Riak Security

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

Users and roles with access to stored procedures

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