DBMS > EJDB vs. FatDB vs. Microsoft SQL Server vs. PouchDB vs. RDF4J

System Properties Comparison EJDB vs. FatDB vs. Microsoft SQL Server vs. PouchDB vs. RDF4J

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Microsofts flagship relational DBMS

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

Document store
Key-value store

Relational DBMS

Document store

RDF store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

github.com/Softmotions/ejdb

www.microsoft.com/en-us/sql-server

pouchdb.com

rdf4j.org

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

learn.microsoft.com/en-US/sql/sql-server

pouchdb.com/guides

rdf4j.org/documentation

Developer

Softmotions

FatCloud

Microsoft

Apache Software Foundation

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

Initial release

2012

1989

2012

2004

Current release

SQL Server 2022, November 2022

7.1.1, June 2019

License

Commercial or Open Source

Open Source

GPLv2

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

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Implementation language

C++

JavaScript

Java

Server operating systems

server-less

Windows

Linux
Windows

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

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

Via inetgration in SQL Server

yes

APIs and other access methods

in-process shared library

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

JavaScript

Java
PHP
Python

Server-side scripts

Stored procedures

yes

via applications

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

View functions in JavaScript

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes, but depending on the SQL-Server Edition

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

User concepts

Access control

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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