DBMS > Drizzle vs. HugeGraph vs. MonetDB vs. ToroDB

System Properties Comparison Drizzle vs. HugeGraph vs. MonetDB vs. ToroDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A fast-speed and highly-scalable Graph DBMS

A relational database management system that stores data in columns

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.monetdb.org

github.com/torodb/server

Technical documentation

hugegraph.apache.org/docs

www.monetdb.org/Documentation

Developer

Drizzle project, originally started by Brian Aker

Baidu

MonetDB BV

8Kdata

Initial release

2008

2018

2004

2016

Current release

7.2.4, September 2012

0.9

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2.0

Open Source

Mozilla Public License 2.0

Open Source

AGPL-V3

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

FreeBSD
Linux
OS X

Linux
macOS
Unix

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

C
C++
Java
PHP

Groovy
Java
Python

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

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes, in SQL, C, R

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

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

none

Source-replica replication available in experimental status

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

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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.

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users, roles and permissions

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

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