DBMS > 4D vs. Couchbase vs. DuckDB vs. Oracle Berkeley DB

System Properties Comparison 4D vs. Couchbase vs. DuckDB vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	2.37
Rank	#110	Overall
	#54	Relational DBMS

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	5.61
Rank	#60	Overall
	#34	Relational DBMS

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Website

www.4d.com

www.couchbase.com

duckdb.org

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

Technical documentation

developer.4d.com

docs.couchbase.com

duckdb.org/docs

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

Developer

4D, Inc

Couchbase, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

1984

2011

2018

1994

Current release

v20, April 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

1.0.0, June 2024

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

MIT License

Open Source

commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Go and Erlang

C++

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

Server operating systems

OS X
Windows

Linux
OS X
Windows

server-less

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

SQL interfaced based on SQLite is available

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.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

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Triggers

yes

via the TAP protocol

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

Source-replica 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
Immediate Consistency

selectable on a per-operation basis

Immediate 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

yes, multi-version concurrency control (MVCC)

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

Ephemeral buckets

yes

User concepts

Access control

Users and groups

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

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