DBMS > 4D vs. Amazon Aurora vs. EsgynDB vs. Qdrant

System Properties Comparison 4D vs. Amazon Aurora vs. EsgynDB vs. Qdrant

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

MySQL and PostgreSQL compatible cloud service by Amazon

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A high-performance vector database with neural network or semantic-based matching

Primary database model

Relational DBMS

Vector DBMS

Secondary database models

Document store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

www.4d.com

aws.amazon.com/rds/aurora

www.esgyn.cn

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

developer.4d.com

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

qdrant.tech/documentation

Developer

4D, Inc

Amazon

Esgyn

Qdrant

Initial release

1984

2015

2021

Current release

v20, April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

C++, Java

Rust

Server operating systems

OS X
Windows

hosted

Linux

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

ADO.NET
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

4D proprietary IDE
PHP

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC/ADO.Net

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

Multi-source replication between multi datacenters

Collection-level replication

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, tunable 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

fine grained access rights according to SQL-standard

Key-based authentication

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

Recent citations in the news

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ...
14 May 2024, AWS Blog

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

New – Amazon Aurora Optimized Reads for Aurora PostgreSQL with up to 8x query latency improvement for I/O ...
8 November 2023, AWS Blog

Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ...
9 February 2024, AWS Blog

Amazon Aurora MySQL zero-ETL integration with Amazon Redshift is now generally available | Amazon Web Services
7 November 2023, AWS Blog

provided by Google News

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, Business Wire

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Qdrant launches first vector database as a managed hybrid cloud
16 April 2024, VentureBeat

Why Vector Data Services For AI Are A Moveable Feast
17 April 2024, Forbes

provided by Google News

Share this page