DBMS > 4D vs. Hazelcast vs. Microsoft Azure SQL Database vs. PouchDB vs. SQLite

System Properties Comparison 4D vs. Hazelcast vs. Microsoft Azure SQL Database vs. PouchDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A widely adopted in-memory data grid

Database as a Service offering with high compatibility to Microsoft SQL Server

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS
Spatial DBMS

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Trend Chart

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.4d.com

hazelcast.com

azure.microsoft.com/en-us/products/azure-sql/database

pouchdb.com

www.sqlite.org

Technical documentation

developer.4d.com

hazelcast.org/imdg/docs

docs.microsoft.com/en-us/azure/azure-sql

pouchdb.com/guides

www.sqlite.org/docs.html

Developer

4D, Inc

Hazelcast

Microsoft

Apache Software Foundation

Dwayne Richard Hipp

Initial release

1984

2008

2010

2012

2000

Current release

v20, April 2023

5.3.6, November 2023

V12

7.1.1, June 2019

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

JavaScript

Server operating systems

OS X
Windows

All OS with a Java VM

hosted

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

server-less

Data scheme

yes

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

4D proprietary IDE
PHP

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Transact SQL

View functions in JavaScript

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Replicated Map

yes, with always 3 replicas available

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

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Users and groups

Role-based access control

fine grained access rights according to SQL-standard

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