DBMS > 4D vs. Amazon Neptune vs. Amazon Redshift vs. FileMaker vs. Riak KV

System Properties Comparison 4D vs. Amazon Neptune vs. Amazon Redshift vs. FileMaker vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Fast, reliable graph database built for the cloud

Large scale data warehouse service for use with business intelligence tools

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

www.4d.com

aws.amazon.com/neptune

aws.amazon.com/redshift

www.claris.com/filemaker

Technical documentation

developer.4d.com

aws.amazon.com/neptune/developer-resources

docs.aws.amazon.com/redshift

www.claris.com/resources/documentation

www.tiot.jp/riak-docs/riak/kv/latest

Developer

4D, Inc

Amazon

Amazon (based on PostgreSQL)

Claris

a subsidiary of Apple

OpenSource, formerly Basho Technologies

Initial release

1984

2017

2012

1983

2009

Current release

v20, April 2023

19.4.1, November 2021

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

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

Erlang

Server operating systems

OS X
Windows

hosted

iOS

client part only
Linux
OS X
Windows

Linux
OS X

Data scheme

yes

schema-free

yes

schema-free

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

A http query request can return the data in XML format

Secondary indexes

yes

restricted

yes

restricted

SQL

Support of SQL

yes

close to SQL 92

yes

does not fully support an SQL-standard

yes

via plugins

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
ODBC

Filemaker WebDirect
JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

4D proprietary IDE
PHP

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC

PHP

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions

in Python

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

yes

Source-replica replication, warm standby

since Version 14

selectable replication factor

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

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

informational only, not enforced by the system

yes

links between data sets can be stored

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

with encyption-at-rest

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

simple rights management via user accounts and connection to external directory services

yes, using Riak Security

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