DBMS > RRDtool vs. Trino vs. Yaacomo

System Properties Comparison RRDtool vs. Trino vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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.

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

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

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	1.70
Rank	#136	Overall
	#11	Time Series DBMS

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

oss.oetiker.ch/rrdtool

trino.io

yaacomo.com

Technical documentation

oss.oetiker.ch/rrdtool/doc

trino.io/broadcast
trino.io/docs/current

Developer

Tobias Oetiker

Trino Software Foundation

Q2WEB GmbH

Initial release

1999

2012

2020 rebranded from PrestoSQL

2009

Current release

1.8.0, 2022

License

Commercial or Open Source

Open Source

GPL V2 and FLOSS

Open Source

Apache Version 2.0

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

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

Java

Server operating systems

HP-UX
Linux

Linux
macOS

for devlopment

Android
Linux
Windows

Data scheme

yes

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.

Exporting into and restoring from XML files possible

Secondary indexes

depending on connected data-source

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library
Pipes

JDBC
RESTful HTTP API
Trino CLI

JDBC
ODBC

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

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on connected data-source

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on connected data-source

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

depending on connected data-source

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

depending on connected data-source

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes

depending on connected data-source

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

SQL standard access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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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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