DBMS > 4D vs. Cubrid vs. GBase vs. Google BigQuery vs. Graph Engine

System Properties Comparison 4D vs. Cubrid vs. GBase vs. Google BigQuery vs. Graph Engine

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Large scale data warehouse service with append-only tables

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

Primary database model

Relational DBMS

Graph DBMS
Key-value store

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Website

www.4d.com

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

www.gbase.cn

cloud.google.com/bigquery

www.graphengine.io

Technical documentation

developer.4d.com

cubrid.org/manuals

cloud.google.com/bigquery/docs

www.graphengine.io/docs/manual

Developer

4D, Inc

CUBRID Corporation, CUBRID Foundation

General Data Technology Co., Ltd.

Google

Microsoft

Initial release

1984

2008

2004

2010

Current release

v20, April 2023

11.0, January 2021

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

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, Java, Python

.NET and C

Server operating systems

OS X
Windows

Linux
Windows

Linux

hosted

.NET

Data scheme

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

Standard with numerous extensions

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
C API
JDBC
ODBC

RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
F#
Visual Basic

Server-side scripts

Stored procedures

yes

Java Stored Procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

In-memory capabilities

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

yes

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

yes

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

Google Cloud Identity & Access Management (IAM)

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