DBMS > H2 vs. HugeGraph vs. MonetDB vs. MySQL

System Properties Comparison H2 vs. HugeGraph vs. MonetDB vs. MySQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A fast-speed and highly-scalable Graph DBMS

A relational database management system that stores data in columns

Widely used open source RDBMS

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.h2database.com

github.com/hugegraph
hugegraph.apache.org

www.monetdb.org

www.mysql.com

Technical documentation

www.h2database.com/html/main.html

hugegraph.apache.org/docs

www.monetdb.org/Documentation

dev.mysql.com/doc

Developer

Thomas Mueller

Baidu

MonetDB BV

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2005

2018

2004

1995

Current release

2.2.220, July 2023

0.9

Dec2023 (11.49), December 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2.0

Open Source

Mozilla Public License 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

Linux
macOS
Unix

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

Groovy
Java
Python

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

asynchronous Gremlin script jobs

yes, in SQL, C, R

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding via remote tables

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Source-replica replication available in experimental status

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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.