DBMS > Blazegraph vs. FatDB vs. InfinityDB vs. NSDb

System Properties Comparison Blazegraph vs. FatDB vs. InfinityDB vs. NSDb

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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.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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 .NET NoSQL DBMS that can integrate with and extend SQL Server.

A Java embedded Key-Value Store which extends the Java Map interface

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Key-value store

Time Series 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	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

blazegraph.com

boilerbay.com

nsdb.io

Technical documentation

wiki.blazegraph.com

boilerbay.com/infinitydb/manual

nsdb.io/Architecture

Developer

Blazegraph

FatCloud

Boiler Bay Inc.

Initial release

2006

2012

2002

2017

Current release

2.1.5, March 2019

4.0

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

Open Source

Apache Version 2.0

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

Java, Scala

Server operating systems

Linux
OS X
Windows

Windows

All OS with a Java VM

Linux
macOS

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

RDF literal types

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes: int, bigint, decimal, string

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

manual creation possible, using inversions based on multi-value capability

all fields are automatically indexed

SQL

Support of SQL

SPARQL is used as query language

Via inetgration in SQL Server

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

gRPC
HTTP REST
WebSocket

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Java

Java
Scala

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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)

Can implement custom security layer via applications

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More resources

Recent citations in the news

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Video: Blazegraph Accelerates Graph Computing with GPUs - High-Performance Computing News Analysis
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

Representation Learning on RDF* and LPG Knowledge Graphs
24 September 2020, Towards Data Science

provided by Google News

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