DBMS > AgensGraph vs. EsgynDB vs. FatDB vs. MonetDB

System Properties Comparison AgensGraph vs. EsgynDB vs. FatDB vs. MonetDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A relational database management system that stores data in columns

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Document store
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	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Website

bitnine.net/agensgraph

www.esgyn.cn

www.monetdb.org

Technical documentation

bitnine.net/documentation

www.monetdb.org/Documentation

Developer

Bitnine Global Inc.

Esgyn

FatCloud

MonetDB BV

Initial release

2016

2015

2012

2004

Current release

2.1, December 2018

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Mozilla Public License 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

C++, Java

Server operating systems

Linux
OS X
Windows

Linux

Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

depending on used data model

yes

schema-free

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

Via inetgration in SQL Server

yes

SQL 2003 with some extensions

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

via applications

yes, in SQL, C, R

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

selectable replication factor

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Graph DBMS Performance Comparison AgensGraph vs. Neo4j
29 June 2017, Business Wire

Bitnine Releases AgensGraph 2.1, the Multi-model Graph Database Optimized for the Legacy Environment
29 January 2019, Business Wire

AGE - The Open Source PostgreSQL Extension For Graph Database Functionality
27 June 2022, iProgrammer

Bitnine: The Newly Revealed 'AI Teacher' Powered by Graph Database Delivers Hyper-Personalized Learning ...
25 March 2019, Business Wire

Bitnine Announces Plans for New Business with Apache AGE's Top-Level Promotion
14 June 2022, Business Wire

provided by Google News

In 2024 the MonetDB Foundation was established for the preservation, maintenance and further development of the ...
31 January 2024, Centrum Wiskunde & Informatica (CWI)

MonetDB Secures Investment From (and Partners With) ServiceNow
9 December 2021, Datanami

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R - Part I - DataScienceCentral.com
6 April 2018, Data Science Central

Test of Time Award for paper on vectorized execution
16 January 2024, Centrum Wiskunde & Informatica (CWI)

How MonetDB Exploits Modern CPU Performance | by Dwi Prasetyo Adi Nugroho
14 January 2020, Towards Data Science

provided by Google News

Share this page