DBMS > Cubrid vs. EsgynDB vs. Firebird vs. Sphinx

System Properties Comparison Cubrid vs. EsgynDB vs. Firebird vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

Search engine

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	21.06
Rank	#31	Overall
	#19	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

cubrid.com (korean)
cubrid.org (english)

www.esgyn.cn

www.firebirdsql.org

sphinxsearch.com

Technical documentation

cubrid.org/manuals

www.firebirdsql.org/en/reference-manuals

sphinxsearch.com/docs

Developer

CUBRID Corporation, CUBRID Foundation

Esgyn

Firebird Foundation

Sphinx Technologies Inc.

Initial release

2008

2015

2000

As fork of Borland's InterBase

2001

Current release

11.0, January 2021

5.0.0, January 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Initial Developer's Public License

Open Source

GPL version 2, commercial licence available

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

C, C++, Java

C++, Java

C and C++

C++

Server operating systems

Linux
Windows

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

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.

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Proprietary protocol

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

PSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of 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

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

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