DBMS > GBase vs. Lovefield vs. MonetDB vs. Tkrzw

System Properties Comparison GBase vs. Lovefield vs. MonetDB vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

An analytical database for business intelligence with large customers in China.

Embeddable relational database for web apps written in pure JavaScript

A relational database management system that stores data in columns

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	1.04
Rank	#190	Overall
	#88	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	1.72
Rank	#148	Overall
	#68	Relational DBMS

Score	0.09
Rank	#354	Overall
	#51	Key-value stores

Website

www.gbase.cn

google.github.io/lovefield

www.monetdb.org

dbmx.net/tkrzw

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

www.monetdb.org/Documentation

Developer

Google

MonetDB BV

Mikio Hirabayashi

Initial release

2014

2004

2020

Current release

GBase 8a

2.1.12, February 2017

Dec2023 (11.49), December 2023

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2.0

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

JavaScript

C++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

schema-free

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

SQL-like query language

via JavaScript builder pattern

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

JavaScript

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

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes, in SQL, C, R

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

none

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

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