DBMS > Blueflood vs. MaxDB vs. RRDtool vs. VelocityDB

System Properties Comparison Blueflood vs. MaxDB vs. RRDtool vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

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.

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Graph DBMS
Object oriented DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

blueflood.io

maxdb.sap.com

oss.oetiker.ch/rrdtool

velocitydb.com

Technical documentation

github.com/rax-maas/blueflood/wiki

maxdb.sap.com/documentation

oss.oetiker.ch/rrdtool/doc

velocitydb.com/UserGuide

Developer

Rackspace

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

Tobias Oetiker

VelocityDB Inc

Initial release

2013

1984

1999

2011

Current release

7.9.10.12, February 2024

1.8.0, 2022

7.x

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Limited community edition free

Open Source

GPL V2 and FLOSS

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

Java

C++

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

Server operating systems

Linux
OS X

AIX
HP-UX
Linux
Solaris
Windows

HP-UX
Linux

Any that supports .NET

Data scheme

predefined scheme

yes

Typing

predefined data types such as float or date

yes

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

HTTP REST

ADO.NET
JDBC
ODBC
WebDAV

in-process shared library
Pipes

.Net

Supported programming languages

.Net
C#
Java
Perl
PHP
Python

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

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

none

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

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

Based on Windows Authentication

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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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