DBMS > Blazegraph vs. FatDB vs. OpenTSDB vs. Postgres-XL

System Properties Comparison Blazegraph vs. FatDB vs. OpenTSDB vs. Postgres-XL

Please select another system to include it in the comparison.

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.

Scalable Time Series DBMS based on HBase

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial 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	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

blazegraph.com

opentsdb.net

www.postgres-xl.org

Technical documentation

wiki.blazegraph.com

opentsdb.net/docs/build/html/index.html

www.postgres-xl.org/documentation

Developer

Blazegraph

FatCloud

currently maintained by Yahoo and other contributors

Initial release

2006

2012

2011

2014

since 2012, originally named StormDB

Current release

2.1.5, March 2019

10 R1, October 2018

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

Open Source

LGPL

Open Source

Mozilla public 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

Server operating systems

Linux
OS X
Windows

Windows

Linux
Windows

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

numeric data for metrics, strings for tags

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

Via inetgration in SQL Server

yes

distributed, parallel query execution

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

HTTP API
Telnet API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Erlang
Go
Java
Python
R
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

via applications

user defined functions

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

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

based on HBase

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

MVCC

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)

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

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

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

A real-time processing revival - O'Reilly Radar
2 April 2015, O'Reilly Radar

provided by Google News

Share this page