DBMS > Amazon Redshift vs. Blazegraph vs. Microsoft Azure Synapse Analytics vs. Netezza

System Properties Comparison Amazon Redshift vs. Blazegraph vs. Microsoft Azure Synapse Analytics vs. Netezza

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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.

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.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

aws.amazon.com/redshift

blazegraph.com

azure.microsoft.com/services/synapse-analytics

www.ibm.com/products/netezza

Technical documentation

docs.aws.amazon.com/redshift

wiki.blazegraph.com

docs.microsoft.com/azure/synapse-analytics

Developer

Amazon (based on PostgreSQL)

Blazegraph

Microsoft

IBM

Initial release

2012

2006

2016

2000

Current release

2.1.5, March 2019

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

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

C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux

included in appliance

Data scheme

yes

schema-free

yes

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL is used as query language

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
JDBC
ODBC

JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C#
Java
PHP

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transact SQL

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in Graphs

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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)

yes

Users with fine-grained authorization concept

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