DBMS > Blueflood vs. Faircom DB vs. NuoDB vs. Oracle NoSQL

System Properties Comparison Blueflood vs. Faircom DB vs. NuoDB vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Key-value store
Relational DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

blueflood.io

www.faircom.com/products/faircom-db

www.3ds.com/nuodb-distributed-sql-database

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

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

doc.nuodb.com

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

Developer

Rackspace

FairCom Corporation

Dassault Systèmes

originally NuoDB, Inc.

Oracle

Initial release

2013

1979

2013

2011

Current release

V12, November 2020

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Restricted, free version available

commercial

limited edition free

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

ANSI C, C++

C++

Java

Server operating systems

Linux
OS X

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
Solaris SPARC/x86

Data scheme

predefined scheme

schema free, schema optional, schema required, partial schema,

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

yes, ANSI SQL Types, JSON, typed binary structures

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 with proprietary extensions

yes

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

data is dynamically stored/cached on the nodes where it is read/written

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

Managed transparently by NuoDB

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

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

tunable from ACID to Eventually Consistent

ACID

tunable commit protocol

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

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

yes

Temporary table

yes

off heap cache

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Standard SQL roles/ privileges, Administrative Users

Access rights for users and roles

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