DBMS > Datomic vs. PouchDB vs. RDF4J vs. WakandaDB

System Properties Comparison Datomic vs. PouchDB vs. RDF4J vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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.

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

Primary database model

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

Score	1.47
Rank	#145	Overall
	#66	Relational DBMS

Score	2.08
Rank	#116	Overall
	#21	Document stores

Score	0.82
Rank	#208	Overall
	#7	RDF stores

Score	0.03
Rank	#361	Overall
	#17	Object oriented DBMS

Website

Technical documentation

docs.datomic.com

pouchdb.com/guides

rdf4j.org/documentation

wakanda.github.io/doc

Developer

Cognitect

Apache Software Foundation

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

Wakanda SAS

Initial release

2012

2004

2012

Current release

1.0.7180, July 2024

7.1.1, June 2019

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

limited edition free

Open Source

Eclipse Distribution License (EDL), v1.0.

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, Clojure

JavaScript

Java

C++, JavaScript

Server operating systems

All OS with a Java VM

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

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

yes

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

yes

SQL

Support of SQL

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

RESTful HTTP API

Supported programming languages

Clojure
Java

JavaScript

Java
PHP
Python

JavaScript

Server-side scripts

Stored procedures

yes

Transaction Functions

View functions in JavaScript

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

yes

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More resources

DB-Engines blog posts

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