DBMS > DataFS vs. Firebird vs. Google BigQuery vs. mSQL vs. OrigoDB

System Properties Comparison DataFS vs. Firebird vs. Google BigQuery vs. mSQL vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Firebird is an open source RDBMS forked from Borland's InterBase

Large scale data warehouse service with append-only tables

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

Primary database model

Object oriented DBMS

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Graph DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

newdatabase.com

www.firebirdsql.org

cloud.google.com/bigquery

hughestech.com.au/products/msql

origodb.com

Technical documentation

dev.mobiland.com/Overview.xsp

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigquery/docs

origodb.com/docs

Developer

Mobiland AG

Firebird Foundation

Google

Hughes Technologies

Robert Friberg et al

Initial release

2018

2000

As fork of Borland's InterBase

2010

1994

2009

under the name LiveDB

Current release

1.1.263, October 2022

5.0.0, January 2024

4.4, October 2021

License

Commercial or Open Source

commercial

Open Source

Initial Developer's Public License

commercial

free licenses can be provided

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

C and C++

Server operating systems

Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

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

Linux
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

RESTful HTTP/JSON API

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net
C
C#
C++
VB.Net

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

Server-side scripts

Stored procedures

PSQL

user defined functions

in JavaScript

yes

Triggers

no, except callback-events from server when changes happened

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

Windows-Profile

Users with fine-grained authorization concept

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Role based authorization

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