DBMS > 4D vs. Couchbase vs. LevelDB vs. Riak KV

System Properties Comparison 4D vs. Couchbase vs. LevelDB vs. Riak KV

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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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Document store

Key-value store

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

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	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

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

Website

www.4d.com

www.couchbase.com

github.com/google/leveldb

Technical documentation

developer.4d.com

docs.couchbase.com

github.com/google/leveldb/blob/main/doc/index.md

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

Developer

4D, Inc

Couchbase, Inc.

Google

OpenSource, formerly Basho Technologies

Initial release

1984

2011

2009

Current release

v20, April 2023

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

1.23, February 2021

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

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

Open Source

BSD

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Go and Erlang

C++

Erlang

Server operating systems

OS X
Windows

Linux
OS X
Windows

Illumos
Linux
OS X
Windows

Linux
OS X

Data scheme

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

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

close to SQL 92

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

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

HTTP API
Native Erlang Interface

Supported programming languages

4D proprietary IDE
PHP

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

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

Erlang

Triggers

yes

via the TAP protocol

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

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
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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 automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

User concepts

Access control

Users and groups

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

yes, using Riak Security

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