DBMS > RRDtool vs. SQLite vs. Tibero vs. Trino

System Properties Comparison RRDtool vs. SQLite vs. Tibero vs. Trino

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Editorial information provided by DB-Engines

Name

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.

Widely used embeddable, in-process RDBMS

A secure RDBMS, designed for easy portability from Oracle

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

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	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

oss.oetiker.ch/rrdtool

www.sqlite.org

us.tmaxsoft.com/products/tibero

trino.io

Technical documentation

oss.oetiker.ch/rrdtool/doc

www.sqlite.org/docs.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

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

Social network pages

Developer

Tobias Oetiker

Dwayne Richard Hipp

TmaxSoft

Trino Software Foundation

Initial release

1999

2000

2003

2012

2020 rebranded from PrestoSQL

Current release

1.8.0, 2022

3.45.3 (15 April 2024), April 2024

6, April 2015

License

Commercial or Open Source

Open Source

GPL V2 and FLOSS

Open Source

Public Domain

commercial

Open Source

Apache Version 2.0

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.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

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

C and Assembler

Java

Server operating systems

HP-UX
Linux

server-less

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS

for devlopment

Data scheme

yes

dynamic column types

yes

Typing

predefined data types such as float or date

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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

yes

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

APIs and other access methods

in-process shared library
Pipes

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

JDBC
RESTful HTTP API
Trino CLI

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

Persistent Stored Procedure (PSM)

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

by range, hash, list or composite

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

depending on connected data-source

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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