DBMS > Cubrid vs. dBASE vs. Google BigQuery vs. Graph Engine vs. MonetDB

System Properties Comparison Cubrid vs. dBASE vs. Google BigQuery vs. Graph Engine vs. MonetDB

Editorial information provided by DB-Engines

Name

Description

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

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

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

A relational database management system that stores data in columns

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

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

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Website

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

www.dbase.com

cloud.google.com/bigquery

www.graphengine.io

www.monetdb.org

Technical documentation

cubrid.org/manuals

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

www.graphengine.io/docs/manual

www.monetdb.org/Documentation

Developer

CUBRID Corporation, CUBRID Foundation

Asthon Tate

Google

Microsoft

MonetDB BV

Initial release

2008

1979

2010

2004

Current release

11.0, January 2021

dBASE 2019, 2019

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

Open Source

Mozilla Public License 2.0

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

.NET and C

Server operating systems

Linux
Windows

DOS

dBase Classic
Windows

dBase Pro

hosted

.NET

FreeBSD
Linux
OS X
Solaris
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

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

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
F#
Visual Basic

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

Server-side scripts

Stored procedures

Java Stored Procedures

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

yes

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication available in experimental status

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

Since BigQuery is designed for querying data

ACID

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 rights for users and roles

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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