DBMS > Faircom DB vs. Firebird vs. openGauss vs. Sequoiadb vs. SQLite

System Properties Comparison Faircom DB vs. Firebird vs. openGauss vs. Sequoiadb vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

NewSQL database with distributed OLTP and SQL

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.faircom.com/products/faircom-db

www.firebirdsql.org

gitee.com/opengauss
opengauss.org

www.sequoiadb.com

www.sqlite.org

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

www.firebirdsql.org/en/reference-manuals

docs.opengauss.org/en
gitee.com/opengauss/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

www.sqlite.org/docs.html

Developer

FairCom Corporation

Firebird Foundation

Huawei and openGauss community

Sequoiadb Ltd.

Dwayne Richard Hipp

Initial release

1979

2000

As fork of Borland's InterBase

2019

2013

2000

Current release

V12, November 2020

5.0.0, January 2024

3.0, March 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Initial Developer's Public License

Open Source

Server: AGPL; Client: Apache V2

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

ANSI C, C++

C and C++

C, C++, Java

C++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

server-less

Data scheme

schema free, schema optional, schema required, partial schema,

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

oid, date, timestamp, binary, regex

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

ANSI SQL 2011

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC

proprietary protocol using JSON

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C
C++
Java

.Net
C++
Java
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

PSQL

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

horizontal partitioning (by range, list and hash)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

yes

via file-system locks

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

Users with fine-grained authorization concept

Access rights for users, groups and roles according to SQL-standard

simple password-based access control

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