DBMS > Graphite vs. Infobright vs. RDF4J

System Properties Comparison Graphite vs. Infobright vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Primary database model

Time Series DBMS

Relational DBMS

RDF store

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

Score	4.81
Rank	#63	Overall
	#4	Time Series DBMS

Score	0.85
Rank	#204	Overall
	#96	Relational DBMS

Score	0.87
Rank	#202	Overall
	#7	RDF stores

Website

github.com/graphite-project/graphite-web

ignitetech.com/softwarelibrary/infobrightdb

rdf4j.org

Technical documentation

graphite.readthedocs.io

rdf4j.org/documentation

Developer

Chris Davis

Ignite Technologies Inc.; formerly InfoBright Inc.

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

Initial release

2006

2005

2004

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

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Implementation language

Python

Java

Server operating systems

Linux
Unix

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

Numeric data only

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API
Sockets

ADO.NET
JDBC
ODBC

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

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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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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Recent citations in the news

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

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20 March 2024, The New Stack

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The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
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