DBMS > Cubrid vs. Google Cloud Firestore vs. Lovefield vs. PostgreSQL vs. SWC-DB

System Properties Comparison Cubrid vs. Google Cloud Firestore vs. Lovefield vs. PostgreSQL vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

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.

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Wide column store

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Time Series DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

firebase.google.com/products/firestore

google.github.io/lovefield

www.postgresql.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

cubrid.org/manuals

firebase.google.com/docs/firestore

github.com/google/lovefield/blob/master/docs/spec_index.md

www.postgresql.org/docs

Developer

CUBRID Corporation, CUBRID Foundation

Google

PostgreSQL Global Development Group

www.postgresql.org/developer

Alex Kashirin

Initial release

2008

2017

2014

1989

1989: Postgres, 1996: PostgreSQL

2020

Current release

11.0, January 2021

2.1.12, February 2017

16.3, May 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

BSD

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++, Java

JavaScript

C++

Server operating systems

Linux
Windows

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

standard with numerous extensions

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Proprietary protocol
Thrift

Supported programming languages

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

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

JavaScript

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

yes, with Cloud Functions

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

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

More information provided by the system vendor

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