DBMS > Amazon Aurora vs. EXASOL vs. Microsoft Azure Cosmos DB vs. PouchDB vs. Snowflake

System Properties Comparison Amazon Aurora vs. EXASOL vs. Microsoft Azure Cosmos DB vs. PouchDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Globally distributed, horizontally scalable, multi-model database service

JavaScript DBMS with an API inspired by CouchDB

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	8.50
Rank	#49	Overall
	#31	Relational DBMS

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.35
Rank	#116	Overall
	#22	Document stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/rds/aurora

www.exasol.com

azure.microsoft.com/services/cosmos-db

pouchdb.com

www.snowflake.com

Technical documentation

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

www.exasol.com/resources

learn.microsoft.com/azure/cosmos-db

pouchdb.com/guides

docs.snowflake.net/manuals/index.html

Developer

Amazon

Exasol

Microsoft

Apache Software Foundation

Snowflake Computing Inc.

Initial release

2015

2000

2014

2012

2014

Current release

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

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

JavaScript

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

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

JSON types

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 properties auto-indexed by default

yes

via views

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

only for PouchDB Server
JavaScript API

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
Lua
Python
R

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

JavaScript

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

JavaScript

View functions in JavaScript

user defined functions

Triggers

yes

JavaScript

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Access rights for users, groups and roles according to SQL-standard

Access rights can be defined down to the item level

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

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