DBMS > Firebase Realtime Database vs. Hawkular Metrics vs. OrigoDB vs. OushuDB vs. TimesTen

System Properties Comparison Firebase Realtime Database vs. Hawkular Metrics vs. OrigoDB vs. OushuDB vs. TimesTen

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 fully ACID in-memory object graph database

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Time Series DBMS

Document store
Object oriented DBMS

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

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.hawkular.org

origodb.com

www.oushu.com/product/oushuDB

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

firebase.google.com/docs/database

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

origodb.com/docs

www.oushu.com/documentation

docs.oracle.com/database/timesten-18.1

Developer

Google

acquired by Google 2014

Community supported by Red Hat

Robert Friberg et al

Oushu

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2014

2009

under the name LiveDB

1998

Current release

4.0.1, August 2020

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

commercial

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

Linux
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

Full-featured ANSI SQL support

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

.NET Client API
HTTP API
LINQ

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java
JavaScript
Objective-C

Go
Java
Python
Ruby

.Net

C
C++

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

PL/SQL

Triggers

Callbacks are triggered when data changes

yes

via Hawkular Alerting

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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 or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

depending on model

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

Write ahead log

yes

by means of logfiles and checkpoints

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

Role based authorization

Kerberos, SSL and role based access

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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