DBMS > Amazon Redshift vs. Blazegraph vs. CouchDB vs. FatDB

System Properties Comparison Amazon Redshift vs. Blazegraph vs. CouchDB vs. FatDB

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Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Large scale data warehouse service for use with business intelligence tools

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Primary database model

Relational DBMS

Graph DBMS
RDF store

Document store

Document store
Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	8.30
Rank	#47	Overall
	#7	Document stores

Website

aws.amazon.com/redshift

blazegraph.com

couchdb.apache.org

Technical documentation

docs.aws.amazon.com/redshift

wiki.blazegraph.com

docs.couchdb.org/en/stable

Developer

Amazon (based on PostgreSQL)

Blazegraph

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

FatCloud

Initial release

2012

2006

2005

2012

Current release

2.1.5, March 2019

3.3.3, December 2023

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

Apache version 2

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

Java

Erlang

Server operating systems

hosted

Linux
OS X
Windows

Android
BSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal 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.

Secondary indexes

restricted

yes

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL is used as query language

Via inetgration in SQL Server

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

RESTful HTTP/JSON API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

user defined functions

in Python

yes

View functions in JavaScript

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in Graphs

Transaction concepts

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

ACID

atomic operations within a single document possible

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

Access rights for users can be defined per database

Can implement custom security layer via applications

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