DBMS > BigObject vs. Firebase Realtime Database vs. GBase vs. OpenQM

System Properties Comparison BigObject vs. Firebase Realtime Database vs. GBase vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Relational DBMS

Multivalue DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

bigobject.io

firebase.google.com/products/realtime-database

www.gbase.cn

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

Technical documentation

docs.bigobject.io

firebase.google.com/docs/database

Developer

BigObject, Inc.

Google

acquired by Google 2014

General Data Technology Co., Ltd.

Rocket Software, originally Martin Phillips

Initial release

2015

2012

2004

1993

Current release

GBase 8a, GBase 8s, GBase 8c

3.4-12

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

GPLv2, extended commercial license available

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

C, Java, Python

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

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

SQL-like DML and DDL statements

Standard with numerous extensions

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

Lua

limited functionality with using 'rules'

user defined functions

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

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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Recent citations in the news

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