DBMS > Firebase Realtime Database vs. Hawkular Metrics vs. Memcached vs. Stardog

System Properties Comparison Firebase Realtime Database vs. Hawkular Metrics vs. Memcached vs. Stardog

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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.

In-memory key-value store, originally intended for caching

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

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

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	20.74
Rank	#32	Overall
	#4	Key-value stores

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

firebase.google.com/products/realtime-database

www.hawkular.org

www.memcached.org

www.stardog.com

Technical documentation

firebase.google.com/docs/database

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

github.com/memcached/memcached/wiki

docs.stardog.com

Developer

Google

acquired by Google 2014

Community supported by Red Hat

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Stardog-Union

Initial release

2012

2014

2003

2010

Current release

1.6.25, March 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD license

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

FreeBSD
Linux
OS X
Unix
Windows

Linux
macOS
Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

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/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

Proprietary protocol

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Java
JavaScript
Objective-C

Go
Java
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

Callbacks are triggered when data changes

yes

via Hawkular Alerting

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication in HA-Cluster

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 in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

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.

yes

User concepts

Access control

yes, based on authentication and database rules

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users and roles

More information provided by the system vendor

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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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Redis extends the lead in the DB-Engines key-value store ranking
3 February 2014, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

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Recent citations in the news

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

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

Millions of user records exposed by 900+ sites via Firebase
18 March 2024, The Register

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

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5 June 2019, DevClass

provided by Google News

Why DDoS Threat Actors Are Shifting Their Tactics
15 March 2024, Infosecurity Magazine

What are memcached servers, and why are they being used to launch record-setting DDoS attacks?
6 March 2018, GeekWire

Memcached DDoS: The biggest, baddest denial of service attacker yet
1 March 2018, ZDNet

Why Redis beats Memcached for caching
14 September 2017, InfoWorld

Memcached 1.6 Released With Enhanced Performance For This Memory Caching System
9 March 2020, Phoronix

provided by Google News

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