DBMS > FatDB vs. MySQL vs. Postgres-XL vs. PouchDB vs. SQream DB

System Properties Comparison FatDB vs. MySQL vs. Postgres-XL vs. PouchDB vs. SQream DB

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

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

Widely used open source RDBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

JavaScript DBMS with an API inspired by CouchDB

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Key-value store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

Technical documentation

dev.mysql.com/doc

www.postgres-xl.org/documentation

pouchdb.com/guides

docs.sqream.com

Developer

FatCloud

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

SQream Technologies

Initial release

2012

1995

2014

since 2012, originally named StormDB

2012

2017

Current release

8.4.0, April 2024

10 R1, October 2018

7.1.1, June 2019

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Mozilla public license

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

JavaScript

C++, CUDA, Haskell, Java, Scala

Server operating systems

Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

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

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

XML type, but no XML query functionality

Secondary indexes

yes

via views

SQL

Support of SQL

Via inetgration in SQL Server

yes

with proprietary extensions

yes

distributed, parallel query execution

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

only for PouchDB Server
JavaScript API

.Net
JDBC
ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

yes

proprietary syntax

user defined functions

View functions in JavaScript

user defined functions in Python

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Can implement custom security layer via applications

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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