DBMS > Amazon Redshift vs. Blazegraph vs. HBase vs. MonetDB vs. Valentina Server

System Properties Comparison Amazon Redshift vs. Blazegraph vs. HBase vs. MonetDB vs. Valentina Server

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.

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.

Wide-column store based on Apache Hadoop and on concepts of BigTable

A relational database management system that stores data in columns

Object-relational database and reports server

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.77
Rank	#222	Overall
	#20	Graph DBMS
	#8	RDF stores

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	1.72
Rank	#148	Overall
	#68	Relational DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

wiki.blazegraph.com

hbase.apache.org/book.html

www.monetdb.org/Documentation

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Amazon (based on PostgreSQL)

Blazegraph

Apache Software Foundation

Apache top-level project, originally developed by Powerset

MonetDB BV

Paradigma Software

Initial release

2012

2006

2008

2004

1999

Current release

2.1.5, March 2019

2.3.4, January 2021

Dec2023 (11.49), December 2023

5.7.5

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

Apache version 2

Open Source

Mozilla Public License 2.0

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

Server operating systems

hosted

Linux
OS X
Windows

Linux
Unix
Windows

using Cygwin

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

RDF literal types

options to bring your own types, AVRO

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

SPARQL is used as query language

yes

SQL 2003 with some extensions

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Java API
RESTful HTTP API
Thrift

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Coprocessors in Java

yes, in SQL, C, R

yes

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

Multi-source replication
Source-replica replication

none

Source-replica replication available in experimental status

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

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

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)

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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