DBMS > Citus vs. Couchbase vs. Faircom DB vs. Newts vs. Oracle NoSQL

System Properties Comparison Citus vs. Couchbase vs. Faircom DB vs. Newts vs. Oracle NoSQL

Editorial information provided by DB-Engines

Name

Description

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

Time Series DBMS 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

Document store

Key-value store
Relational DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

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

Website

www.citusdata.com

www.couchbase.com

www.faircom.com/products/faircom-db

opennms.github.io/newts

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

Technical documentation

docs.citusdata.com

docs.couchbase.com

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

github.com/OpenNMS/newts/wiki

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

Developer

Couchbase, Inc.

FairCom Corporation

OpenNMS Group

Oracle

Initial release

2010

2011

1979

2014

2011

Current release

8.1, December 2018

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

V12, November 2020

23.3, December 2023

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Restricted, free version available

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++, Go and Erlang

ANSI C, C++

Java

Server operating systems

Linux

Linux
OS X
Windows

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

easily portable to other OSs

Linux
OS X
Windows

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

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

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

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes, ANSI SQL with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

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

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

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

HTTP REST
Java API

RESTful HTTP API

Supported programming languages

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

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

Java

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.

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

.Net, JavaScript, C/C++

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

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

Multi-source replication

including cross data center replication
Source-replica replication

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

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

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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

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

tunable from ACID to Eventually Consistent

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

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

Ephemeral buckets

yes

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

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

Access rights for users and roles

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