DBMS > Couchbase vs. Netezza

System Properties Comparison Couchbase vs. Netezza

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with a powerful search engine and in-built operational and analytical capabilities

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store

Relational DBMS

Secondary database models

Key-value store

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

using the Geocouch extension

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

Score	25.34
Rank	#31	Overall
	#5	Document stores

Score	15.88
Rank	#39	Overall
	#24	Relational DBMS

Website

www.couchbase.com

www.ibm.com/products/netezza

Technical documentation

docs.couchbase.com

Developer

Couchbase, Inc.

IBM

Initial release

2011

2000

Current release

Server: 7.0, July 2021; Mobile: 3, February 2022; Couchbase Capella, October 2021

License

Commercial or Open Source

Open Source

Apache version 2; Commercial licenses also available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Go and Erlang

Server operating systems

Linux
OS X
Windows

Linux

included in appliance

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

String, Boolean, Number

yes

Secondary indexes

yes

SQL

Support of SQL

Declarative query language (N1QL) that extends ANSI SQL to JSON. First commercial implementation of SQL++.

yes

APIs and other access methods

Native language bindings for CRUD, Query, Search and Analytics APIs

JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

Functions and timers in JavaScript

yes

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

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

Ephemeral buckets

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication

Users with fine-grained authorization concept

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