DBMS > Blazegraph vs. FatDB vs. OpenTenBase vs. Yaacomo

System Properties Comparison Blazegraph vs. FatDB vs. OpenTenBase vs. Yaacomo

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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.

Yaacomo seems to be discontinued and is removed 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 .NET NoSQL DBMS that can integrate with and extend SQL Server.

An enterprise-level distributed HTAP open source database based on PostgreSQL

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Relational DBMS

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

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

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

blazegraph.com

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

yaacomo.com

Technical documentation

wiki.blazegraph.com

docs.opentenbase.org
docs.opentenbase.org/en

Developer

Blazegraph

FatCloud

OpenAtom Foundation, previously Tencent

Q2WEB GmbH

Initial release

2006

2012

2009

Current release

2.1.5, March 2019

2.5, January 2024

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

Open Source

BSD-3

commercial

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

Server operating systems

Linux
OS X
Windows

Windows

Linux

Android
Linux
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

Via inetgration in SQL Server

yes

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

JDBC
ODBC

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
Go
Java
PHP
Python

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

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 or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

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

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)

Can implement custom security layer via applications

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

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

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

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

Faster with GPUs: 5 turbocharged databases
26 September 2016, InfoWorld

provided by Google News

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