DBMS > Hawkular Metrics vs. Prometheus vs. RRDtool vs. SpaceTime

System Properties Comparison Hawkular Metrics vs. Prometheus vs. RRDtool vs. SpaceTime

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Editorial information provided by DB-Engines

Name

Description

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Open-source Time Series DBMS and monitoring 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.

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Time Series DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	7.92
Rank	#51	Overall
	#2	Time Series DBMS

Score	2.14
Rank	#124	Overall
	#10	Time Series DBMS

Score	0.00
Rank	#396	Overall
	#8	Spatial DBMS

Website

www.hawkular.org

prometheus.io

oss.oetiker.ch/rrdtool

www.mireo.com/spacetime

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

prometheus.io/docs

oss.oetiker.ch/rrdtool/doc

Developer

Community supported by Red Hat

Tobias Oetiker

Mireo

Initial release

2014

2015

1999

2020

Current release

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

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

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

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

HP-UX
Linux

Linux

Data scheme

schema-free

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.

Import of XML data possible

Exporting into and restoring from XML files possible

Secondary indexes

SQL

Support of SQL

A subset of ANSI SQL is implemented

APIs and other access methods

HTTP REST

RESTful HTTP/JSON API

in-process shared library
Pipes

RESTful HTTP API

Supported programming languages

Go
Java
Python
Ruby

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

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++
Python

Server-side scripts

Stored procedures

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

by Federation

none

Real-time block device replication (DRBD)

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

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

yes

More information provided by the system vendor

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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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