DBMS > Cubrid vs. DolphinDB vs. Hive vs. NSDb

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

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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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Primary database model

Secondary database models

Relational DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

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

www.dolphindb.com

hive.apache.org

nsdb.io

Technical documentation

cubrid.org/manuals

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

cwiki.apache.org/confluence/display/Hive/Home

nsdb.io/Architecture

Developer

CUBRID Corporation, CUBRID Foundation

DolphinDB, Inc

Apache Software Foundation

initially developed by Facebook

Initial release

2008

2018

2012

2017

Current release

11.0, January 2021

v2.00.4, January 2022

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

Apache Version 2

Open Source

Apache Version 2.0

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++

Java

Java, Scala

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

SQL

Support of SQL

yes

SQL-like query language

SQL-like DML and DDL statements

SQL-like query language

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

JDBC
ODBC
Thrift

gRPC
HTTP REST
WebSocket

Supported programming languages

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

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

C++
Java
PHP
Python

Java
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

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

Access rights for users, groups and roles

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More resources

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