DBMS > Oracle NoSQL vs. PostGIS vs. PouchDB vs. SQLite vs. WakandaDB

System Properties Comparison Oracle NoSQL vs. PostGIS vs. PouchDB vs. SQLite vs. WakandaDB

Editorial information provided by DB-Engines

Name

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

Spatial extension of PostgreSQL

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Key-value store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

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

Technical documentation

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

postgis.net/documentation

pouchdb.com/guides

www.sqlite.org/docs.html

wakanda.github.io/doc

Developer

Oracle

Apache Software Foundation

Dwayne Richard Hipp

Wakanda SAS

Initial release

2011

2005

2012

2000

2012

Current release

23.3, December 2023

3.4.2, February 2024

7.1.1, June 2019

3.46.0 (23 May 2024), May 2024

2.7.0 (April 29, 2019), April 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

GPL v2.0

Open Source

Public Domain

Open Source

AGPLv3, extended commercial license available

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

Java

JavaScript

C++, JavaScript

Server operating systems

Linux
Solaris SPARC/x86

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

server-less

Linux
OS X
Windows

Data scheme

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

yes

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

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

RESTful HTTP API

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

Sharding

with a proxy-based framework, named couchdb-lounge

none

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

yes

based on PostgreSQL

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

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

yes

based on PostgreSQL

yes

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