DBMS > DolphinDB vs. mSQL vs. openGemini vs. Sadas Engine

System Properties Comparison DolphinDB vs. mSQL vs. openGemini vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

mSQL (Mini SQL) is a simple and lightweight RDBMS

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

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

Primary database model

Secondary database models

Relational DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

www.dolphindb.com

hughestech.com.au/products/msql

www.opengemini.org
github.com/openGemini

www.sadasengine.com

Technical documentation

docs.dolphindb.cn/en/help200/index.html

docs.opengemini.org/guide

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

Developer

DolphinDB, Inc

Hughes Technologies

Huawei and openGemini community

SADAS s.r.l.

Initial release

2018

1994

2022

2006

Current release

v2.00.4, January 2022

4.4, October 2021

1.1, July 2023

8.0

License

Commercial or Open Source

commercial

free community version available

commercial

free licenses can be provided

Open Source

Apache Version 2.0

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++

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
ODBC

HTTP REST

JDBC
ODBC
Proprietary protocol

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

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

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

Administrators, Users, Groups

Administrators and common users accounts

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

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