DBMS > Firebase Realtime Database vs. Hawkular Metrics vs. HEAVY.AI vs. OrigoDB

System Properties Comparison Firebase Realtime Database vs. Hawkular Metrics vs. HEAVY.AI vs. OrigoDB

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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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A fully ACID in-memory object graph database

Primary database model

Document store

Time Series DBMS

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Spatial DBMS

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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

firebase.google.com/products/realtime-database

www.hawkular.org

github.com/heavyai/heavydb
www.heavy.ai

origodb.com

Technical documentation

firebase.google.com/docs/database

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

docs.heavy.ai

origodb.com/docs

Developer

Google

acquired by Google 2014

Community supported by Red Hat

HEAVY.AI, Inc.

Robert Friberg et al

Initial release

2012

2014

2016

2009

under the name LiveDB

Current release

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

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

C++ and CUDA

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

JDBC
ODBC
Thrift
Vega

.NET Client API
HTTP API
LINQ

Supported programming languages

Java
JavaScript
Objective-C

Go
Java
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

.Net

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

via Hawkular Alerting

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Round robin

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

Source-replica replication

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

depending on model

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

Write ahead log

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

Role based authorization

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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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