DBMS > Cubrid vs. DolphinDB vs. HugeGraph vs. mSQL vs. Riak TS

System Properties Comparison Cubrid vs. DolphinDB vs. HugeGraph vs. mSQL vs. Riak TS

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.

A fast-speed and highly-scalable Graph DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

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

www.dolphindb.com

github.com/hugegraph
hugegraph.apache.org

hughestech.com.au/products/msql

Technical documentation

cubrid.org/manuals

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

hugegraph.apache.org/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

CUBRID Corporation, CUBRID Foundation

DolphinDB, Inc

Baidu

Hughes Technologies

Open Source, formerly Basho Technologies

Initial release

2008

2018

1994

2015

Current release

11.0, January 2021

v2.00.4, January 2022

0.9

4.4, October 2021

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

Apache Version 2.0

commercial

free licenses can be provided

Open Source

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

Erlang

Server operating systems

Linux
Windows

Linux
macOS
Unix

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

Linux
OS X

Data scheme

yes

schema-free

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

also supports composite index and range index

yes

restricted

SQL

Support of SQL

yes

SQL-like query language

A subset of ANSI SQL is implemented

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

yes, limited

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

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

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

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

Groovy
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

yes

asynchronous Gremlin script jobs

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

links between datasets can be stored

Transaction concepts

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

ACID

yes

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

Users, roles and permissions

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