DBMS > 4D vs. Drizzle vs. HEAVY.AI vs. mSQL vs. PostgreSQL

System Properties Comparison 4D vs. Drizzle vs. HEAVY.AI vs. mSQL vs. PostgreSQL

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Application development environment with integrated database management system

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used open source RDBMS

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

Primary database model

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

Spatial 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	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

www.4d.com

github.com/heavyai/heavydb
www.heavy.ai

hughestech.com.au/products/msql

www.postgresql.org

Technical documentation

developer.4d.com

docs.heavy.ai

www.postgresql.org/docs

Developer

4D, Inc

Drizzle project, originally started by Brian Aker

HEAVY.AI, Inc.

Hughes Technologies

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

1984

2008

2016

1994

1989

1989: Postgres, 1996: PostgreSQL

Current release

v20, April 2023

7.2.4, September 2012

5.10, January 2022

4.4, October 2021

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache Version 2; enterprise edition available

commercial

free licenses can be provided

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

C++ and CUDA

Server operating systems

OS X
Windows

FreeBSD
Linux
OS X

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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

Data scheme

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

yes

with proprietary extensions

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

standard with numerous extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC

JDBC
ODBC
Thrift
Vega

JDBC
ODBC

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

Supported programming languages

4D proprietary IDE
PHP

C
C++
Java
PHP

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

.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

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

Multi-source replication

none

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

none

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.

yes

User concepts

Access control

Users and groups

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

More information provided by the system vendor

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