DBMS > EsgynDB vs. Graph Engine vs. MonetDB vs. Oracle Rdb

System Properties Comparison EsgynDB vs. Graph Engine vs. MonetDB vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

Description

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

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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

www.esgyn.cn

www.graphengine.io

www.monetdb.org

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

Technical documentation

www.graphengine.io/docs/manual

www.monetdb.org/Documentation

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Esgyn

Microsoft

MonetDB BV

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2015

2010

2004

1984

Current release

Dec2023 (11.49), December 2023

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Mozilla Public License 2.0

commercial

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

.NET and C

Server operating systems

Linux

.NET

FreeBSD
Linux
OS X
Solaris
Windows

HP Open VMS

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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

yes

SQL 2003 with some extensions

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
F#
Visual Basic

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

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