DBMS > FatDB vs. Graphite vs. OpenTSDB vs. RDF4J

System Properties Comparison FatDB vs. Graphite vs. OpenTSDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Scalable Time Series DBMS based on HBase

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Key-value store

Time Series DBMS

RDF store

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

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

github.com/graphite-project/graphite-web

opentsdb.net

rdf4j.org

Technical documentation

graphite.readthedocs.io

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

rdf4j.org/documentation

Developer

FatCloud

Chris Davis

currently maintained by Yahoo and other contributors

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2012

2006

2011

2004

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

LGPL

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Python

Java

Server operating systems

Windows

Linux
Unix

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

APIs and other access methods

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

HTTP API
Sockets

HTTP API
Telnet API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

JavaScript (Node.js)
Python

Erlang
Go
Java
Python
R
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

via applications

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

none

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Can implement custom security layer via applications

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More resources

DB-Engines blog posts

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

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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

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