DBMS > Firebase Realtime Database vs. Hawkular Metrics vs. SAP SQL Anywhere vs. SiteWhere

System Properties Comparison Firebase Realtime Database vs. Hawkular Metrics vs. SAP SQL Anywhere vs. SiteWhere

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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.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

M2M integration platform for persisting/querying time series data

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	4.57
Rank	#78	Overall
	#43	Relational DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Website

firebase.google.com/products/realtime-database

www.hawkular.org

www.sap.com/products/technology-platform/sql-anywhere.html

github.com/sitewhere/sitewhere

Technical documentation

firebase.google.com/docs/database

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

help.sap.com/docs/SAP_SQL_Anywhere

sitewhere1.sitewhere.io/index.html

Developer

Google

acquired by Google 2014

Community supported by Red Hat

SAP

formerly Sybase

SiteWhere

Initial release

2012

2014

1992

2010

Current release

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

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
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

predefined scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

ADO.NET
HTTP API
JDBC
ODBC

HTTP REST

Supported programming languages

Java
JavaScript
Objective-C

Go
Java
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes, in C/C++, Java, .Net or Perl

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

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

Database mirroring

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

Foreign keys

Referential integrity

yes

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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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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