DBMS > Cachelot.io vs. CouchDB vs. EventStoreDB vs. Hawkular Metrics vs. Netezza

System Properties Comparison Cachelot.io vs. CouchDB vs. EventStoreDB vs. Hawkular Metrics vs. Netezza

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Website

www.ibm.com/products/netezza

Technical documentation

docs.couchdb.org/en/stable

developers.eventstore.com

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Event Store Limited

Community supported by Red Hat

IBM

Initial release

2015

2005

2012

2014

2000

Current release

3.3.3, December 2023

21.2, February 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

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++

Erlang

Java

Server operating systems

FreeBSD
Linux
OS X

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X
Windows

Linux

included in appliance

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

Memcached protocol

RESTful HTTP/JSON API

HTTP REST

JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Go
Java
Python
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

improved architecture with release 2.0

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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.

User concepts

Access control

Access rights for users can be defined per database

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month
2 June 2014, Matthias Gelbmann

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Recent citations in the news

How to install the CouchDB NoSQL database on Debian Server 11
16 June 2022, TechRepublic

IBM Cloudant pulls plan to fund new foundational layer for CouchDB
15 March 2022, The Register

CouchDB 3.0 ends admin party era
27 February 2020, DevClass

Hadoop, CouchDB Next Targets in Wave of Database Attacks
20 January 2017, Threatpost

How to Connect Your Flask App With CouchDB: A NoSQL Database - MUO
14 August 2021, MakeUseOf

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Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived…
5 June 2019, DevClass

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Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, ibm.com

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, Microsoft

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

provided by Google News

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