DBMS > Amazon Redshift vs. Cubrid vs. Google Cloud Firestore vs. IBM Db2 vs. Quasardb

System Properties Comparison Amazon Redshift vs. Cubrid vs. Google Cloud Firestore vs. IBM Db2 vs. Quasardb

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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Common in IBM host environments, 2 different versions for host and Windows/Linux

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Time Series DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/redshift

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

firebase.google.com/products/firestore

www.ibm.com/products/db2

quasar.ai

Technical documentation

docs.aws.amazon.com/redshift

cubrid.org/manuals

firebase.google.com/docs/firestore

www.ibm.com/docs/en/db2

doc.quasar.ai/master

Developer

Amazon (based on PostgreSQL)

CUBRID Corporation, CUBRID Foundation

Google

IBM

quasardb

Initial release

2012

2008

2017

1983

host version

2009

Current release

11.0, January 2021

12.1, October 2016

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

hosted

Linux
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

only with Windows/Unix/Linux Version

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

yes

with separate tools (MQ, InfoSphere)

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

with Hadoop integration

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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