DBMS > 4D vs. Riak KV vs. Trafodion vs. Vitess

System Properties Comparison 4D vs. Riak KV vs. Trafodion vs. Vitess

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Application development environment with integrated database management system

Distributed, fault tolerant key-value store

Transactional SQL-on-Hadoop DBMS

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Key-value store

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

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

www.4d.com

trafodion.apache.org

vitess.io

Technical documentation

developer.4d.com

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

trafodion.apache.org/documentation.html

vitess.io/docs

Developer

4D, Inc

OpenSource, formerly Basho Technologies

Apache Software Foundation, originally developed by HP

The Linux Foundation, PlanetScale

Initial release

1984

2009

2014

2013

Current release

v20, April 2023

3.2.0, December 2022

2.3.0, February 2019

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache 2.0

Open Source

Apache Version 2.0, commercial licenses 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

Erlang

C++, Java

Server operating systems

OS X
Windows

Linux
OS X

Linux

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

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

yes

SQL

Support of SQL

yes

close to SQL 92

yes

with proprietary extensions

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

4D proprietary IDE
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

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

yes

Erlang

Java Stored Procedures

yes

proprietary syntax

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

yes, via HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Users and groups

yes, using Riak Security

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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