DBMS > Amazon DocumentDB vs. BigchainDB vs. PouchDB vs. RDF4J vs. Sequoiadb

System Properties Comparison Amazon DocumentDB vs. BigchainDB vs. PouchDB vs. RDF4J vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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.

NewSQL database with distributed OLTP and SQL

Primary database model

Document store

RDF store

Document store
Relational DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

aws.amazon.com/documentdb

Technical documentation

aws.amazon.com/documentdb/resources

bigchaindb.readthedocs.io/en/latest

pouchdb.com/guides

rdf4j.org/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Apache Software Foundation

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

Sequoiadb Ltd.

Initial release

2019

2016

2012

2004

2013

Current release

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

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

Python

JavaScript

Java

C++

Server operating systems

hosted

Linux

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

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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 query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

CLI Client
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

proprietary protocol using JSON

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Go
Haskell
Java
JavaScript
Python
Ruby

JavaScript

Java
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

User concepts

Access control

Access rights for users and roles

yes

simple password-based access control

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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