DBMS > HyperSQL vs. openGauss vs. Oracle NoSQL

System Properties Comparison HyperSQL vs. openGauss vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.70
Rank	#92	Overall
	#49	Relational DBMS

Score	0.94
Rank	#187	Overall
	#85	Relational DBMS

Score	3.43
Rank	#75	Overall
	#13	Document stores
	#9	Key-value stores
	#40	Relational DBMS

Website

hsqldb.org

gitee.com/opengauss
opengauss.org

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

docs.opengauss.org/en
gitee.com/opengauss/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Huawei and openGauss community

Oracle

Initial release

2001

2019

2011

Current release

2.7.2, June 2023

3.0, March 2022

24.4, December 2024

License

Commercial or Open Source

Open Source

based on BSD license

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Java

C, C++, Java

Java

Server operating systems

All OS with a Java VM

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

Linux

Linux
Solaris SPARC/x86

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

ANSI SQL 2011

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC
Java

C
C++
Java

C#
Go
Java
JavaScript (Node.js)
Python
Rust
Typescript (Node.js)

Server-side scripts

Stored procedures

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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