DBMS > Cubrid vs. DolphinDB vs. Sequoiadb vs. SpatiaLite

System Properties Comparison Cubrid vs. DolphinDB vs. Sequoiadb vs. SpatiaLite

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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.

NewSQL database with distributed OLTP and SQL

Spatial extension of SQLite

Primary database model

Relational DBMS

Time Series DBMS

Document store
Relational DBMS

Spatial 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	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

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

www.dolphindb.com

www.sequoiadb.com

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

cubrid.org/manuals

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

www.sequoiadb.com/en/index.php?m=Files&a=index

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

CUBRID Corporation, CUBRID Foundation

DolphinDB, Inc

Sequoiadb Ltd.

Alessandro Furieri

Initial release

2008

2018

2013

2008

Current release

11.0, January 2021

v2.00.4, January 2022

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

Server: AGPL; Client: Apache V2

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

Server operating systems

Linux
Windows

Linux

server-less

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

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

proprietary protocol using JSON

Supported programming languages

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

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Document is locked during a transaction

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

fine grained access rights according to SQL-standard

Administrators, Users, Groups

simple password-based access control

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