DBMS > Oracle NoSQL vs. PouchDB vs. SQLite vs. Trafodion

System Properties Comparison Oracle NoSQL vs. PouchDB vs. SQLite vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Key-value store
Relational DBMS

Document store

Relational DBMS

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

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Score	2.35
Rank	#116	Overall
	#22	Document stores

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

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

pouchdb.com

www.sqlite.org

trafodion.apache.org

Technical documentation

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

pouchdb.com/guides

www.sqlite.org/docs.html

trafodion.apache.org/documentation.html

Developer

Oracle

Apache Software Foundation

Dwayne Richard Hipp

Apache Software Foundation, originally developed by HP

Initial release

2011

2012

2000

2014

Current release

23.3, December 2023

7.1.1, June 2019

3.45.3 (15 April 2024), April 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Public Domain

Open Source

Apache 2.0

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++, Java

Server operating systems

Linux
Solaris SPARC/x86

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

server-less

Linux

Data scheme

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

optional

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

yes

APIs and other access methods

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
Go
Java
JavaScript (Node.js)
Python

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

View functions in JavaScript

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

off heap cache

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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