DBMS > Hive vs. openGauss vs. OpenQM vs. RocksDB

System Properties Comparison Hive vs. openGauss vs. OpenQM vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Multivalue DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

hive.apache.org

gitee.com/opengauss
opengauss.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

rocksdb.org

Technical documentation

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

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

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

initially developed by Facebook

Huawei and openGauss community

Rocket Software, originally Martin Phillips

Facebook, Inc.

Initial release

2012

2019

1993

2013

Current release

3.1.3, April 2022

3.0, March 2022

3.4-12

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPLv2, extended commercial license available

Open Source

BSD

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

C++

Server operating systems

All OS with a Java VM

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL 2011

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
ODBC

C++ API
Java API

Supported programming languages

C++
Java
PHP
Python

C
C++
Java

.Net
Basic
C
Java
Objective C
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash)

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes

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

Eventual Consistency

Immediate 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

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

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

Access rights can be defined down to the item level

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