DBMS > Cubrid vs. Google BigQuery vs. Google Cloud Firestore vs. Graph Engine vs. Typesense

System Properties Comparison Cubrid vs. Google BigQuery vs. Google Cloud Firestore vs. Graph Engine vs. Typesense

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Relational DBMS

Document store

Graph DBMS
Key-value store

Search engine

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

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

cloud.google.com/bigquery

firebase.google.com/products/firestore

www.graphengine.io

typesense.org

Technical documentation

cubrid.org/manuals

cloud.google.com/bigquery/docs

firebase.google.com/docs/firestore

www.graphengine.io/docs/manual

typesense.org/docs

Developer

CUBRID Corporation, CUBRID Foundation

Google

Microsoft

Initial release

2008

2010

2017

2010

2015

Current release

11.0, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

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

.NET and C

C++

Server operating systems

Linux
Windows

hosted

.NET

Linux

Data scheme

yes

schema-free

yes

schema-free

pre-defined schema optional

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

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP/JSON API

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

RESTful HTTP API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C#
C++
F#
Visual Basic

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Multi-source replication using RAFT

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

Since BigQuery is designed for querying data

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.