DBMS > 4D vs. Amazon Neptune vs. DataFS vs. Oracle Berkeley DB

System Properties Comparison 4D vs. Amazon Neptune vs. DataFS vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Fast, reliable graph database built for the cloud

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Widely used in-process key-value store

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Graph DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

www.4d.com

aws.amazon.com/neptune

newdatabase.com

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

developer.4d.com

aws.amazon.com/neptune/developer-resources

dev.mobiland.com/Overview.xsp

docs.oracle.com/cd/E17076_05/html/index.html

Developer

4D, Inc

Amazon

Mobiland AG

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

1984

2017

2018

1994

Current release

v20, April 2023

1.1.263, October 2022

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

commercial license available

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, C++ (depending on the Berkeley DB edition)

Server operating systems

OS X
Windows

hosted

Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

SQL interfaced based on SQLite is available

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

.NET Client API
Proprietary client DLL
WinRT client

Supported programming languages

4D proprietary IDE
PHP

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C#
C++
VB.Net

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

no, except callback-events from server when changes happened

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Proprietary Sharding system

none

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.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

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)

Windows-Profile

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More resources

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