DBMS > Cubrid vs. DolphinDB vs. NSDb vs. OpenMLDB

System Properties Comparison Cubrid vs. DolphinDB vs. NSDb vs. OpenMLDB

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

An open-source machine learning database that provides a feature platform for training and inference

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Website

cubrid.com (korean)
cubrid.org (english)

www.dolphindb.com

nsdb.io

openmldb.ai

Technical documentation

cubrid.org/manuals

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

nsdb.io/Architecture

openmldb.ai/docs/zh/main

Developer

CUBRID Corporation, CUBRID Foundation

DolphinDB, Inc

4 Paradigm Inc.

Initial release

2008

2018

2017

2020

Current release

11.0, January 2021

v2.00.4, January 2022

2024-2 February 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

Apache Version 2.0

Open Source

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++, Java

C++

Java, Scala

C++, Java, Scala

Server operating systems

Linux
Windows

Linux
macOS

Linux

Data scheme

yes

Fixed schema

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, 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

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

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

gRPC
HTTP REST
WebSocket

JDBC
SQLAlchemy

Supported programming languages

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

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

Java
Scala

C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

fine grained access rights according to SQL-standard

Administrators, Users, Groups

fine grained access rights according to SQL-standard

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