DBMS > 4D vs. Amazon Redshift vs. Graph Engine vs. Informix vs. Quasardb

System Properties Comparison 4D vs. Amazon Redshift vs. Graph Engine vs. Informix vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Large scale data warehouse service for use with business intelligence tools

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	17.87
Rank	#35	Overall
	#22	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

www.4d.com

aws.amazon.com/redshift

www.graphengine.io

www.ibm.com/products/informix

quasar.ai

Technical documentation

developer.4d.com

docs.aws.amazon.com/redshift

www.graphengine.io/docs/manual

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

doc.quasar.ai/master

Developer

4D, Inc

Amazon (based on PostgreSQL)

Microsoft

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

quasardb

Initial release

1984

2012

2010

1984

2009

Current release

v20, April 2023

14.10.FC5, November 2020

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

free developer edition available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

.NET and C

C, C++ and Java

C++

Server operating systems

OS X
Windows

hosted

.NET

AIX
HP-UX
Linux
macOS
Solaris
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

close to SQL 92

yes

does not fully support an SQL-standard

yes

SQL-like query language

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

RESTful HTTP API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

Users with fine-grained authentication, authorization, and auditing controls

Cryptographically strong user authentication and audit trail

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