DBMS > FatDB vs. RRDtool vs. SiriDB vs. TerminusDB

System Properties Comparison FatDB vs. RRDtool vs. SiriDB vs. TerminusDB

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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.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Open Source Time Series DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store
Key-value store

Time Series DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

oss.oetiker.ch/rrdtool

siridb.com

terminusdb.com

Technical documentation

oss.oetiker.ch/rrdtool/doc

docs.siridb.com

terminusdb.github.io/terminusdb/#

Developer

FatCloud

Tobias Oetiker

Cesbit

DataChemist Ltd.

Initial release

2012

1999

2017

2018

Current release

1.8.0, 2022

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

GPL V2 and FLOSS

Open Source

MIT License

Open Source

GPL V3

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

Implementations in Java (e.g. RRD4J) and C# available

Prolog, Rust

Server operating systems

Windows

HP-UX
Linux

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

Numeric data

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language (WOQL)

APIs and other access methods

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

in-process shared library
Pipes

HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

JavaScript
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

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

Journaling Streams

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

Can implement custom security layer via applications

simple rights management via user accounts

Role-based access control

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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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