DBMS > Drizzle vs. HugeGraph vs. HyperSQL vs. VoltDB

System Properties Comparison Drizzle vs. HugeGraph vs. HyperSQL vs. VoltDB

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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.

Description

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

A fast-speed and highly-scalable Graph DBMS

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

hsqldb.org

www.voltdb.com

Technical documentation

hugegraph.apache.org/docs

hsqldb.org/web/hsqlDocsFrame.html

docs.voltdb.com

Developer

Drizzle project, originally started by Brian Aker

Baidu

VoltDB Inc.

Initial release

2008

2018

2001

2010

Current release

7.2.4, September 2012

0.9

2.7.2, June 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

FreeBSD
Linux
OS X

Linux
macOS
Unix

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X

for development

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.

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

only a subset of SQL 99

APIs and other access methods

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API

JDBC via HTTP
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C++
Java
PHP

Groovy
Java
Python

All languages supporting JDBC/ODBC
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Java, SQL

Java

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

none

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

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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Recent citations in the news

POC exploit code published for 9.8-rated Apache HugeGraph RCE flaw
7 June 2024, The Register

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
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provided by Google News

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