DBMS > Cubrid vs. Firebird vs. Google BigQuery vs. HEAVY.AI

System Properties Comparison Cubrid vs. Firebird vs. Google BigQuery vs. HEAVY.AI

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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

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

Large scale data warehouse service with append-only tables

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	21.06
Rank	#31	Overall
	#19	Relational DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Website

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

www.firebirdsql.org

cloud.google.com/bigquery

github.com/heavyai/heavydb
www.heavy.ai

Technical documentation

cubrid.org/manuals

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigquery/docs

docs.heavy.ai

Developer

CUBRID Corporation, CUBRID Foundation

Firebird Foundation

Google

HEAVY.AI, Inc.

Initial release

2008

2000

As fork of Borland's InterBase

2010

2016

Current release

11.0, January 2021

5.0.0, January 2024

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Initial Developer's Public License

commercial

Open Source

Apache Version 2; enterprise edition 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, C++, Java

C and C++

C++ and CUDA

Server operating systems

Linux
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

Linux

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

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

Supported programming languages

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

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

Java Stored Procedures

PSQL

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Since BigQuery is designed for querying data

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

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

Users with fine-grained authorization concept

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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