DBMS > Amazon Redshift vs. Fauna vs. HugeGraph vs. RavenDB

System Properties Comparison Amazon Redshift vs. Fauna vs. HugeGraph vs. RavenDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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.

A fast-speed and highly-scalable Graph DBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Graph DBMS

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

aws.amazon.com/redshift

fauna.com

github.com/hugegraph
hugegraph.apache.org

ravendb.net

Technical documentation

docs.aws.amazon.com/redshift

docs.fauna.com

hugegraph.apache.org/docs

ravendb.net/docs

Developer

Amazon (based on PostgreSQL)

Fauna, Inc.

Baidu

Hibernating Rhinos

Initial release

2012

2014

2018

2010

Current release

0.9

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

AGPL version 3, commercial license available

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

Java

Server operating systems

hosted

Linux
macOS
Unix

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Groovy
Java
Python

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

edges in graph

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

Identity management, authentication, and access control

Users, roles and permissions

Authorization levels configured per client per database

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