DBMS > Blueflood vs. Cubrid vs. FatDB vs. mSQL vs. Oracle NoSQL

System Properties Comparison Blueflood vs. Cubrid vs. FatDB vs. mSQL vs. Oracle NoSQL

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Time Series DBMS

Relational DBMS

Document store
Key-value store

Relational DBMS

Document store
Key-value store
Relational DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

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

Website

blueflood.io

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

hughestech.com.au/products/msql

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

Technical documentation

github.com/rax-maas/blueflood/wiki

cubrid.org/manuals

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

Developer

Rackspace

CUBRID Corporation, CUBRID Foundation

FatCloud

Hughes Technologies

Oracle

Initial release

2013

2008

2012

1994

2011

Current release

11.0, January 2021

4.4, October 2021

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

free licenses can be provided

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

Linux
OS X

Linux
Windows

Windows

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

Linux
Solaris SPARC/x86

Data scheme

predefined scheme

yes

schema-free

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

Via inetgration in SQL Server

A subset of ANSI SQL is implemented

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

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC
OLE DB

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

C
C++
Delphi
Java
Perl
PHP
Tcl

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

selectable replication factor

none

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

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency
Immediate Consistency

none

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

Can implement custom security layer via applications

Access rights for users and roles

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