DBMS > Cubrid vs. GBase vs. Google BigQuery vs. Oracle NoSQL vs. TimesTen

System Properties Comparison Cubrid vs. GBase vs. Google BigQuery vs. Oracle NoSQL vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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 multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

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

www.gbase.cn

cloud.google.com/bigquery

www.oracle.com/database/nosql/technologies/nosql

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

cubrid.org/manuals

cloud.google.com/bigquery/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.oracle.com/database/timesten-18.1

Developer

CUBRID Corporation, CUBRID Foundation

General Data Technology Co., Ltd.

Google

Oracle

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2008

2004

2010

2011

1998

Current release

11.0, January 2021

GBase 8a, GBase 8s, GBase 8c

23.3, December 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

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

Java

Server operating systems

Linux
Windows

Linux

hosted

Linux
Solaris SPARC/x86

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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

Standard with numerous extensions

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
C API
JDBC
ODBC

RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency or Eventual Consistency depending on configuration

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

off heap cache

yes

User concepts

Access control

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)

Access rights for users and roles

fine grained access rights according to SQL-standard

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