DBMS > H2 vs. Netezza vs. PouchDB vs. RocksDB

System Properties Comparison H2 vs. Netezza vs. PouchDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.h2database.com

www.ibm.com/products/netezza

pouchdb.com

rocksdb.org

Technical documentation

www.h2database.com/html/main.html

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

Developer

Thomas Mueller

IBM

Apache Software Foundation

Facebook, Inc.

Initial release

2005

2000

2012

2013

Current release

2.2.220, July 2023

7.1.1, June 2019

9.2.1, May 2024

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

Java

JavaScript

C++

Server operating systems

All OS with a Java VM

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

JDBC
ODBC
OLE DB

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

Supported programming languages

Java

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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