DBMS > Amazon DynamoDB vs. Oracle NoSQL vs. PouchDB vs. RDF4J

System Properties Comparison Amazon DynamoDB vs. Oracle NoSQL vs. PouchDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Key-value store

Document store
Key-value store
Relational DBMS

Document store

RDF store

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

aws.amazon.com/dynamodb

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

pouchdb.com

rdf4j.org

Technical documentation

docs.aws.amazon.com/dynamodb

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

pouchdb.com/guides

rdf4j.org/documentation

Developer

Amazon

Oracle

Apache Software Foundation

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2012

2011

2012

2004

Current release

24.1, May 2024

7.1.1, June 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

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

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

JavaScript

Java

Server operating systems

hosted

Linux
Solaris SPARC/x86

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

Linux
OS X
Unix
Windows

Data scheme

schema-free

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

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

optional

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

APIs and other access methods

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

JavaScript

Java
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

configurable

ACID within a storage node (=shard)

ACID

Isolation support depends on the API used

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 storage is supported as well

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 can be defined via the AWS Identity and Access Management (IAM)

Access rights for users and roles

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