DBMS > Citus vs. Cubrid vs. Hawkular Metrics vs. Oracle NoSQL

System Properties Comparison Citus vs. Cubrid vs. Hawkular Metrics vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Time Series DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store

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

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Website

www.citusdata.com

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

www.hawkular.org

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

Technical documentation

docs.citusdata.com

cubrid.org/manuals

www.hawkular.org/hawkular-metrics/docs/user-guide

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

Developer

CUBRID Corporation, CUBRID Foundation

Community supported by Red Hat

Oracle

Initial release

2010

2008

2014

2011

Current release

8.1, December 2018

11.0, January 2021

23.3, December 2023

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

C, C++, Java

Java

Server operating systems

Linux

Linux
Windows

Linux
OS X
Windows

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
OLE DB

HTTP REST

RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Go
Java
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Java Stored Procedures

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

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 and roles

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