DBMS > Fujitsu Enterprise Postgres vs. Oracle vs. PouchDB vs. SWC-DB

System Properties Comparison Fujitsu Enterprise Postgres vs. Oracle vs. PouchDB vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Widely used RDBMS

JavaScript DBMS with an API inspired by CouchDB

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Document store

Wide column store

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Time Series DBMS

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

Score	0.22
Rank	#304	Overall
	#137	Relational DBMS

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

www.postgresql.fastware.com

www.oracle.com/database

pouchdb.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

www.postgresql.fastware.com/product-manuals

docs.oracle.com/en/database

pouchdb.com/guides

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Oracle

Apache Software Foundation

Alex Kashirin

Initial release

1980

2012

2020

Current release

Fujitsu Enterprise Postgres 14, January 2022

23c, September 2023

7.1.1, June 2019

0.5, April 2021

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL V3

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

C and C++

JavaScript

C++

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

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

Linux

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

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.

yes

Secondary indexes

yes

via views

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

only for PouchDB Server
JavaScript API

Proprietary protocol
Thrift

Supported programming languages

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

JavaScript

C++

Server-side scripts

Stored procedures

user defined functions

PL/SQL

also stored procedures in Java possible

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding, horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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