DBMS > Amazon Redshift vs. EXASOL vs. Fauna

System Properties Comparison Amazon Redshift vs. EXASOL vs. Fauna

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Primary database model

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Website

aws.amazon.com/redshift

www.exasol.com

fauna.com

Technical documentation

docs.aws.amazon.com/redshift

www.exasol.com/resources

docs.fauna.com

Developer

Amazon (based on PostgreSQL)

Exasol

Fauna, Inc.

Initial release

2012

2000

2014

License

Commercial or Open Source

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

Scala

Server operating systems

hosted

Data scheme

yes

schema-free

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java
Lua
Python
R

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

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

Identity management, authentication, and access control

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