DBMS > 4D vs. Apache Phoenix vs. MySQL vs. Riak TS vs. Transbase

System Properties Comparison 4D vs. Apache Phoenix vs. MySQL vs. Riak TS vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A scale-out RDBMS with evolutionary schema built on Apache HBase

Widely used open source RDBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

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	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.4d.com

phoenix.apache.org

www.mysql.com

www.transaction.de/en/products/transbase.html

Technical documentation

developer.4d.com

phoenix.apache.org

dev.mysql.com/doc

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

www.transaction.de/en/products/transbase/features.html

Developer

4D, Inc

Apache Software Foundation

Oracle

since 2010, originally MySQL AB, then Sun

Open Source, formerly Basho Technologies

Transaction Software GmbH

Initial release

1984

2014

1995

2015

1987

Current release

v20, April 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

8.4.0, April 2024

3.0.0, September 2022

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

commercial

free development license

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

Erlang

C and C++

Server operating systems

OS X
Windows

Linux
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

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

yes, limited

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes

proprietary syntax

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

links between datasets can be stored

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

yes

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Users and groups

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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