DBMS > Blazegraph vs. HyperSQL vs. Netezza vs. Transbase

System Properties Comparison Blazegraph vs. HyperSQL vs. Netezza vs. Transbase

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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

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Data warehouse and analytics appliance part of IBM PureSystems

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Graph DBMS
RDF store

Relational DBMS

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

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

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

blazegraph.com

hsqldb.org

www.ibm.com/products/netezza

www.transaction.de/en/products/transbase.html

Technical documentation

wiki.blazegraph.com

hsqldb.org/web/hsqlDocsFrame.html

www.transaction.de/en/products/transbase/features.html

Developer

Blazegraph

IBM

Transaction Software GmbH

Initial release

2006

2001

2000

1987

Current release

2.1.5, March 2019

2.7.2, June 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

based on BSD license

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux

included in appliance

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

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

yes

SQL

Support of SQL

SPARQL is used as query language

yes

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

yes

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

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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More resources

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