DBMS > 4D vs. Dolt vs. H2 vs. NuoDB vs. Riak KV

System Properties Comparison 4D vs. Dolt vs. H2 vs. NuoDB vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A MySQL compatible DBMS with Git-like versioning of data and schema

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Key-value store

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

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	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

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

Website

www.4d.com

github.com/dolthub/dolt
www.dolthub.com

www.h2database.com

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

developer.4d.com

docs.dolthub.com

www.h2database.com/html/main.html

doc.nuodb.com

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

Developer

4D, Inc

DoltHub Inc

Thomas Mueller

Dassault Systèmes

originally NuoDB, Inc.

OpenSource, formerly Basho Technologies

Initial release

1984

2018

2005

2013

2009

Current release

v20, April 2023

2.2.220, July 2023

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

limited edition free

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

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

Implementation language

Java

C++

Erlang

Server operating systems

OS X
Windows

Linux
macOS
Windows

All OS with a Java VM

hosted

Amazon EC2, Windows Azure, SoftLayer
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

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

CLI Client
HTTP REST

JDBC
ODBC

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

4D proprietary IDE
PHP

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

Java

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

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

currently in alpha release

Java Stored Procedures and User-Defined Functions

Java, SQL

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

data is dynamically stored/cached on the nodes where it is read/written

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Managed transparently by NuoDB

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

links between data sets can be stored

Transaction concepts

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

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC

yes

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

Temporary table

User concepts

Access control

Users and groups

Only one user is configurable, and must be specified in the config file at startup

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

yes, using Riak Security

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