DBMS > RRDtool vs. TimesTen vs. Yaacomo vs. Yanza

System Properties Comparison RRDtool vs. TimesTen vs. Yaacomo vs. Yanza

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Editorial information provided by DB-Engines

Name

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

Yanza seems to be discontinued. Therefore it is excluded 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.

In-Memory RDBMS compatible to Oracle

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

Time Series DBMS for IoT Applications

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

oss.oetiker.ch/rrdtool

www.oracle.com/database/technologies/related/timesten.html

yaacomo.com

yanza.com

Technical documentation

oss.oetiker.ch/rrdtool/doc

docs.oracle.com/database/timesten-18.1

Developer

Tobias Oetiker

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Q2WEB GmbH

Yanza

Initial release

1999

1998

2009

2015

Current release

1.8.0, 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GPL V2 and FLOSS

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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

Server operating systems

HP-UX
Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Android
Linux
Windows

Windows

Data scheme

yes

schema-free

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

yes

SQL

Support of SQL

yes

APIs and other access methods

in-process shared library
Pipes

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

HTTP API

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++
Java
PL/SQL

any language that supports HTTP calls

Server-side scripts

Stored procedures

PL/SQL

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

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 or Eventual Consistency depending on configuration

Immediate Consistency

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

by means of logfiles and checkpoints

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

fine grained access rights according to SQL-standard

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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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