DBMS > Netezza vs. PouchDB vs. RocksDB

System Properties Comparison Netezza vs. PouchDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Data warehouse and analytics appliance part of IBM PureSystems

JavaScript DBMS with an API inspired by CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Document store

Key-value store

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

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Score	2.35
Rank	#116	Overall
	#22	Document stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

www.ibm.com/products/netezza

pouchdb.com

rocksdb.org

Technical documentation

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

Developer

IBM

Apache Software Foundation

Facebook, Inc.

Initial release

2000

2012

2013

Current release

7.1.1, June 2019

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C++

Server operating systems

Linux

included in appliance

server-less, requires a JavaScript environment (browser, Node.js)

Linux

Data scheme

yes

schema-free

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

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC
OLE DB

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept

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