DBMS > Blazegraph vs. IRONdb vs. Netezza vs. Transbase

System Properties Comparison Blazegraph vs. IRONdb 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.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

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

Score	0.74
Rank	#217	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

blazegraph.com

www.circonus.com/solutions/time-series-database/

www.ibm.com/products/netezza

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

Technical documentation

wiki.blazegraph.com

docs.circonus.com/irondb/category/getting-started

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

Developer

Blazegraph

Circonus LLC.

IBM

Transaction Software GmbH

Initial release

2006

2017

2000

1987

Current release

2.1.5, March 2019

V0.10.20, January 2018

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

extended commercial license available

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

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

text, numeric, histograms

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HTTP API

JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

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

Server-side scripts

Stored procedures

yes

yes, in Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

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 per node, eventual consistency across nodes

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.

User concepts

Access control

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

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Video: Blazegraph Accelerates Graph Computing with GPUs
20 December 2015, insideHPC

Harnessing GPUs Delivers a Big Speedup for Graph Analytics
15 December 2015, Datanami

This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

provided by Google News

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, azure.microsoft.com

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

provided by Google News

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