DBMS > 4D vs. Amazon DynamoDB vs. Cubrid vs. Heroic vs. MySQL

System Properties Comparison 4D vs. Amazon DynamoDB vs. Cubrid vs. Heroic vs. MySQL

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Widely used open source RDBMS

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.4d.com

aws.amazon.com/dynamodb

cubrid.com (korean)
cubrid.org (english)

github.com/spotify/heroic

www.mysql.com

Technical documentation

developer.4d.com

docs.aws.amazon.com/dynamodb

cubrid.org/manuals

spotify.github.io/heroic

dev.mysql.com/doc

Developer

4D, Inc

Amazon

CUBRID Corporation, CUBRID Foundation

Spotify

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

1984

2012

2008

2014

1995

Current release

v20, April 2023

11.0, January 2021

8.4.0, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Java

C and C++

Server operating systems

OS X
Windows

hosted

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

via Elasticsearch

yes

SQL

Support of SQL

yes

close to SQL 92

yes

with proprietary extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

4D proprietary IDE
PHP

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Source-replica replication

yes

Multi-source replication
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

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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 can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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