DBMS > Amazon Redshift vs. Cubrid vs. Firebird vs. HEAVY.AI

System Properties Comparison Amazon Redshift vs. Cubrid vs. Firebird vs. HEAVY.AI

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

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	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	21.06
Rank	#31	Overall
	#19	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Website

aws.amazon.com/redshift

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

www.firebirdsql.org

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

Technical documentation

docs.aws.amazon.com/redshift

cubrid.org/manuals

www.firebirdsql.org/en/reference-manuals

docs.heavy.ai

Developer

Amazon (based on PostgreSQL)

CUBRID Corporation, CUBRID Foundation

Firebird Foundation

HEAVY.AI, Inc.

Initial release

2012

2008

2000

As fork of Borland's InterBase

2016

Current release

11.0, January 2021

5.0.0, January 2024

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Initial Developer's Public License

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

hosted

Linux
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
Thrift
Vega

Supported programming languages

All languages supporting JDBC/ODBC

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

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

PSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

informational only, not enforced by the system

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

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

fine grained access rights according to SQL-standard

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