DBMS > Drizzle vs. EsgynDB vs. ReductStore vs. VelocityDB

System Properties Comparison Drizzle vs. EsgynDB vs. ReductStore vs. VelocityDB

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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.

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS
Object oriented DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#16	Object oriented DBMS

Website

www.esgyn.cn

github.com/reductstore
www.reduct.store

velocitydb.com

Technical documentation

www.reduct.store/docs

velocitydb.com/UserGuide

Developer

Drizzle project, originally started by Brian Aker

Esgyn

ReductStore LLC

VelocityDB Inc

Initial release

2008

2015

2023

2011

Current release

7.2.4, September 2012

1.9, March 2024

7.x

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Business Source License 1.1

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java

C++, Rust

Server operating systems

FreeBSD
Linux
OS X

Linux

Docker
Linux
macOS
Windows

Any that supports .NET

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

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

HTTP API

.Net

Supported programming languages

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

C++
JavaScript (Node.js)
Python
Rust

.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

hooks for callbacks inside the server can be used.

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

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

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

fine grained access rights according to SQL-standard

Based on Windows Authentication

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