DBMS > Firebase Realtime Database vs. Hawkular Metrics vs. OpenQM vs. OpenTSDB

System Properties Comparison Firebase Realtime Database vs. Hawkular Metrics vs. OpenQM vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Scalable Time Series DBMS based on HBase

Primary database model

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

firebase.google.com/products/realtime-database

www.hawkular.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

opentsdb.net

Technical documentation

firebase.google.com/docs/database

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

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

Developer

Google

acquired by Google 2014

Community supported by Red Hat

Rocket Software, originally Martin Phillips

currently maintained by Yahoo and other contributors

Initial release

2012

2014

1993

2011

Current release

3.4-12

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

LGPL

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
Windows

Data scheme

schema-free

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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.

yes

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

HTTP API
Telnet API

Supported programming languages

Java
JavaScript
Objective-C

Go
Java
Python
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

yes, based on authentication and database rules

Access rights can be defined down to the item level

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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

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Recent citations in the news

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

Don't be like these 900+ websites and expose millions of passwords via Firebase
18 March 2024, The Register

Atos cybersecurity blog: Misconfigured Firebase: A real-time cyber threat
18 January 2024, Atos

Google Firebase may have exposed 125M records from misconfigurations
19 March 2024, SC Media

Hundreds of Google Firebase websites might have leaked data online
19 March 2024, TechRadar

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
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

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

Comparing InfluxDB, TimescaleDB, and QuestDB Timeseries Databases
30 June 2021, Towards Data Science

MakeMyTrip travels forward in time using the power of open source
16 May 2017, Open Source For You

provided by Google News

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