DBMS > Hawkular Metrics vs. OpenTSDB vs. RDF4J vs. STSdb

System Properties Comparison Hawkular Metrics vs. OpenTSDB vs. RDF4J vs. STSdb

Please select another system to include it in the comparison.

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.

Scalable Time Series DBMS based on HBase

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Time Series DBMS

RDF store

Key-value store

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

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

www.hawkular.org

opentsdb.net

rdf4j.org

github.com/STSSoft/STSdb4

Technical documentation

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

opentsdb.net/docs/build/html/index.html

rdf4j.org/documentation

Developer

Community supported by Red Hat

currently maintained by Yahoo and other contributors

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

STS Soft SC

Initial release

2014

2011

2004

2011

Current release

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

LGPL

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPLv2, commercial license available

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

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Windows

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

HTTP REST

HTTP API
Telnet API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.NET Client API

Supported programming languages

Go
Java
Python
Ruby

Erlang
Go
Java
Python
R
Ruby

Java
PHP
Python

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

based on HBase

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

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

User concepts

Access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

Recent citations in the news

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived…
5 June 2019, DevClass

provided by Google News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

provided by Google News

Share this page