DBMS > 4D vs. Apache Druid vs. DataFS vs. PostgreSQL

System Properties Comparison 4D vs. Apache Druid vs. DataFS vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Object oriented DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Graph DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

Technical documentation

developer.4d.com

druid.apache.org/docs/latest/design

dev.mobiland.com/Overview.xsp

www.postgresql.org/docs

Developer

4D, Inc

Apache Software Foundation and contributors

Mobiland AG

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

1984

2012

2018

1989

1989: Postgres, 1996: PostgreSQL

Current release

v20, April 2023

29.0.1, April 2024

1.1.263, October 2022

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

Server operating systems

OS X
Windows

Linux
OS X
Unix

Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

schema-less columns are supported

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL for querying

yes

standard with numerous extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
RESTful HTTP/JSON API

.NET Client API
Proprietary client DLL
WinRT client

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

Supported programming languages

4D proprietary IDE
PHP

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
VB.Net

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

Proprietary Sharding system

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, via HDFS, S3 or other storage engines

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Users and groups

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Windows-Profile

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

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Conferences, events and webinars

more DBMS events

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

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