DBMS > MaxDB vs. mSQL vs. ReductStore vs. RRDtool

System Properties Comparison MaxDB vs. mSQL vs. ReductStore vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

A robust and reliable RDBMS optimized to run all major SAP solutions

mSQL (Mini SQL) is a simple and lightweight RDBMS

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

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.

Primary database model

Relational DBMS

Time Series DBMS

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

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

maxdb.sap.com

hughestech.com.au/products/msql

github.com/reductstore
www.reduct.store

oss.oetiker.ch/rrdtool

Technical documentation

maxdb.sap.com/documentation

www.reduct.store/docs

oss.oetiker.ch/rrdtool/doc

Developer

SAP, acquired from Software AG (Adabas-D) in 1997

Hughes Technologies

ReductStore LLC

Tobias Oetiker

Initial release

1984

1994

2023

1999

Current release

7.9.10.12, February 2024

4.4, October 2021

1.9, March 2024

1.8.0, 2022

License

Commercial or Open Source

commercial

Limited community edition free

commercial

free licenses can be provided

Open Source

Business Source License 1.1

Open Source

GPL V2 and FLOSS

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

C++

C++, Rust

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

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows

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

Docker
Linux
macOS
Windows

HP-UX
Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

ADO.NET
JDBC
ODBC
WebDAV

JDBC
ODBC

HTTP API

in-process shared library
Pipes

Supported programming languages

.Net
C#
Java
Perl
PHP
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

C++
JavaScript (Node.js)
Python
Rust

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

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

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Durability

Support for making data persistent

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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