DBMS > Amazon Redshift vs. Blazegraph vs. Brytlyt vs. FoundationDB vs. MonetDB

System Properties Comparison Amazon Redshift vs. Blazegraph vs. Brytlyt vs. FoundationDB vs. MonetDB

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.

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in 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.

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Ordered key-value store. Core features are complimented by layers.

A relational database management system that stores data in columns

Primary database model

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	22.42
Rank	#33	Overall
	#19	Relational DBMS

Score	0.80
Rank	#190	Overall
	#16	Graph DBMS
	#8	RDF stores

Score	0.40
Rank	#248	Overall
	#115	Relational DBMS

Score	1.07
Rank	#165	Overall
	#27	Document stores
	#28	Key-value stores
	#82	Relational DBMS

Score	2.05
Rank	#115	Overall
	#55	Relational DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

wiki.blazegraph.com

apple.github.io/foundationdb

www.monetdb.org/Documentation

Developer

Amazon (based on PostgreSQL)

Blazegraph

Brytlyt

FoundationDB

MonetDB BV

Initial release

2012

2006

2016

2013

2004

Current release

2.1.5, March 2019

0.9, October 2016

6.2.28, November 2020

Oct2020-SP2, January 2021

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

commercial

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

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

Java

C, C++ and CUDA

C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

some layers support typing

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

specific XML-type available, but no XML query functionality.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL is used as query language

yes

supported in specific SQL layer only

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions

in PL/pgSQL

in SQL-layer only

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Linearizable consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in Graphs

yes

in SQL-layer only

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

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Column-store In-memory optimized GeoSpatial support JSON document support
» more

Competitive advantages

Scalable architecture - vertical data organization and in-memory optimization guarantee...
» more

Typical application scenarios

Analytical database, Data warehouse, OLAP Data mining Scientific database
» more

Key customers

Numascale , Spinque , SecurActive , CHS , NOZHUP
» more

Licensing and pricing models

Free and open-source software, Mozilla Public License 2.0 Commercial support available
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