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

System Properties Comparison Cubrid vs. Google Cloud Firestore vs. KeyDB vs. Lovefield 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.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Embeddable relational database for web apps written in pure JavaScript

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

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	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

firebase.google.com/products/firestore

github.com/Snapchat/KeyDB
keydb.dev

google.github.io/lovefield

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

Technical documentation

cubrid.org/manuals

firebase.google.com/docs/firestore

docs.keydb.dev

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

Developer

CUBRID Corporation, CUBRID Foundation

Google

EQ Alpha Technology Ltd.

Google

Alex Kashirin

Initial release

2008

2017

2019

2014

2020

Current release

11.0, January 2021

2.1.12, February 2017

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD-3

Open Source

Apache 2.0

Open Source

GPL V3

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++

JavaScript

C++

Server operating systems

Linux
Windows

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

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

Proprietary protocol

RESP - REdis Serialization Protoco

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

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript

C++

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

Lua

Triggers

yes

yes, with Cloud Functions

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

none

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
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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.

simple password-based access control and ACL

More information provided by the system vendor

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Related products and services

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More resources

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