DBMS > GBase vs. MonetDB vs. Oracle NoSQL vs. PouchDB

System Properties Comparison GBase vs. MonetDB vs. Oracle NoSQL vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

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

A relational database management system that stores data in columns

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

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Website

www.gbase.cn

www.monetdb.org

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

pouchdb.com

Technical documentation

www.monetdb.org/Documentation

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

pouchdb.com/guides

Developer

General Data Technology Co., Ltd.

MonetDB BV

Oracle

Apache Software Foundation

Initial release

2004

2011

2012

Current release

GBase 8a, GBase 8s, GBase 8c

Dec2023 (11.49), December 2023

24.1, May 2024

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

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

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, Java, Python

Java

JavaScript

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

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

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

yes

optional

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

via views

SQL

Support of SQL

Standard with numerous extensions

yes

SQL 2003 with some extensions

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

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

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes, in SQL, C, R

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding via remote tables

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

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

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

yes

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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