DBMS > Amazon Redshift vs. EsgynDB vs. Fauna vs. H2GIS

System Properties Comparison Amazon Redshift vs. EsgynDB vs. Fauna vs. H2GIS

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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.

Spatial extension of H2

Primary database model

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

aws.amazon.com/redshift

www.esgyn.cn

fauna.com

www.h2gis.org

Technical documentation

docs.aws.amazon.com/redshift

docs.fauna.com

www.h2gis.org/docs/home

Developer

Amazon (based on PostgreSQL)

Esgyn

Fauna, Inc.

CNRS

Initial release

2012

2015

2014

2013

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

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++, Java

Scala

Java

Server operating systems

hosted

Linux

hosted

Data scheme

yes

schema-free

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Java

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

user defined functions

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

Multi-source replication

yes

based on H2

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes, multi-version concurrency control (MVCC)

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

Identity management, authentication, and access control

yes

based on H2

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