DBMS > Cubrid vs. etcd vs. Faircom DB vs. Google Cloud Firestore vs. PostGIS

System Properties Comparison Cubrid vs. etcd vs. Faircom DB vs. Google Cloud Firestore vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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.

Spatial extension of PostgreSQL

Primary database model

Relational DBMS

Key-value store

Key-value store
Relational DBMS

Document store

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

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

etcd.io
github.com/etcd-io/etcd

www.faircom.com/products/faircom-db

firebase.google.com/products/firestore

postgis.net

Technical documentation

cubrid.org/manuals

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

firebase.google.com/docs/firestore

postgis.net/documentation

Developer

CUBRID Corporation, CUBRID Foundation

FairCom Corporation

Google

Initial release

2008

1979

2017

2005

Current release

11.0, January 2021

3.4, August 2019

V12, November 2020

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Restricted, free version available

commercial

Open Source

GPL v2.0

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

ANSI C, C++

Server operating systems

Linux
Windows

FreeBSD
Linux
Windows

experimental

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

hosted

Data scheme

yes

schema-free

schema free, schema optional, schema required, partial schema,

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

Secondary indexes

yes

SQL

Support of SQL

yes

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

gRPC
JSON over HTTP

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

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

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes

yes, watching key changes

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Multi-source replication

yes

based on PostgreSQL

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

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

tunable from ACID to Eventually Consistent

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

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

yes

based on PostgreSQL

More information provided by the system vendor

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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