DBMS > Apache Doris vs. Cubrid vs. HyperSQL vs. Lovefield

System Properties Comparison Apache Doris vs. Cubrid vs. HyperSQL vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

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Trend Chart

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

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

hsqldb.org

google.github.io/lovefield

Technical documentation

github.com/apache/doris/wiki

cubrid.org/manuals

hsqldb.org/web/hsqlDocsFrame.html

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Apache Software Foundation, originally contributed from Baidu

CUBRID Corporation, CUBRID Foundation

Google

Initial release

2017

2008

2001

2014

Current release

1.2.2, February 2023

11.0, January 2021

2.7.2, June 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

Apache 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

Java

C, C++, Java

Java

JavaScript

Server operating systems

Linux

Linux
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
MySQL client

ADO.NET
JDBC
ODBC
OLE DB

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

Java

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

All languages supporting JDBC/ODBC
Java

JavaScript

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Java, SQL

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

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1 September 2023, KDnuggets

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