DBMS > 4D vs. Amazon DocumentDB vs. Amazon Redshift vs. Yaacomo

System Properties Comparison 4D vs. Amazon DocumentDB vs. Amazon Redshift vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Application development environment with integrated database management system

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Large scale data warehouse service for use with business intelligence tools

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Document store

Relational DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Website

www.4d.com

aws.amazon.com/documentdb

aws.amazon.com/redshift

yaacomo.com

Technical documentation

developer.4d.com

aws.amazon.com/documentdb/resources

docs.aws.amazon.com/redshift

Developer

4D, Inc

Amazon (based on PostgreSQL)

Q2WEB GmbH

Initial release

1984

2019

2012

2009

Current release

v20, April 2023

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

OS X
Windows

hosted

Android
Linux
Windows

Data scheme

yes

schema-free

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

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

close to SQL 92

yes

does not fully support an SQL-standard

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC

Server-side scripts

Stored procedures

yes

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomic single-document operations

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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