DBMS > 4D vs. Apache Druid vs. MongoDB vs. PostgreSQL vs. TerminusDB

System Properties Comparison 4D vs. Apache Druid vs. MongoDB vs. PostgreSQL vs. TerminusDB

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

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Widely used open source RDBMS

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

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

Graph DBMS

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Document store
RDF store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

Technical documentation

developer.4d.com

druid.apache.org/docs/latest/design

www.mongodb.com/docs/manual

www.postgresql.org/docs

terminusdb.github.io/terminusdb/#

Developer

4D, Inc

Apache Software Foundation and contributors

MongoDB, Inc

PostgreSQL Global Development Group

www.postgresql.org/developer

DataChemist Ltd.

Initial release

1984

2012

2009

1989

1989: Postgres, 1996: PostgreSQL

2018

Current release

v20, April 2023

29.0.1, April 2024

6.0.7, June 2023

16.3, May 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

BSD

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

C++

Prolog, Rust

Server operating systems

OS X
Windows

Linux
OS X
Unix

Linux
OS X
Solaris
Windows

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

Linux

Data scheme

yes

schema-less columns are supported

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

standard with numerous extensions

SQL-like query language (WOQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
RESTful HTTP/JSON API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

4D proprietary IDE
PHP

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript
Python

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions

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

yes

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

manual/auto, time-based

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

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

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, via HDFS, S3 or other storage engines

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

in-memory journaling

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Users and groups

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

Access rights for users and roles

fine grained access rights according to SQL-standard

Role-based access control

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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