DBMS > Amazon Aurora vs. MySQL vs. NSDb vs. SAP SQL Anywhere vs. Snowflake

System Properties Comparison Amazon Aurora vs. MySQL vs. NSDb vs. SAP SQL Anywhere vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Widely used open source RDBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/rds/aurora

www.mysql.com

nsdb.io

www.sap.com/products/technology-platform/sql-anywhere.html

www.snowflake.com

Technical documentation

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

dev.mysql.com/doc

nsdb.io/Architecture

help.sap.com/docs/SAP_SQL_Anywhere

docs.snowflake.net/manuals/index.html

Developer

Amazon

Oracle

since 2010, originally MySQL AB, then Sun

SAP

formerly Sybase

Snowflake Computing Inc.

Initial release

2015

1995

2017

1992

2014

Current release

8.3.0, January 2024

17, July 2015

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Java, Scala

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

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

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
HTTP REST
WebSocket

ADO.NET
HTTP API
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

Java
Scala

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

yes, in C/C++, Java, .Net or Perl

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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 with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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

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