DBMS > Drizzle vs. Galaxybase vs. ReductStore vs. Sadas Engine

System Properties Comparison Drizzle vs. Galaxybase vs. ReductStore vs. Sadas Engine

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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.

Scalable, ACID-compliant native distributed parallel graph platform

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.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

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

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

galaxybase.com

github.com/reductstore
www.reduct.store

www.sadasengine.com

Technical documentation

www.reduct.store/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Drizzle project, originally started by Brian Aker

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

ReductStore LLC

SADAS s.r.l.

Initial release

2008

2017

2023

2006

Current release

7.2.4, September 2012

Nov 20, November 2021

1.9, March 2024

8.0

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Business Source License 1.1

commercial

free trial version 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.

Implementation language

C++

C and Java

C++, Rust

C++

Server operating systems

FreeBSD
Linux
OS X

Linux

Docker
Linux
macOS
Windows

AIX
Linux
Windows

Data scheme

yes

Strong typed schema

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

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
C++
Java
PHP

Go
Java
Python

C++
JavaScript (Node.js)
Python
Rust

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined procedures and functions

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

managed by 'Learn by Usage'

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role-based access control

Access rights for users, groups and roles according to SQL-standard

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