DBMS > FoundationDB vs. Lovefield vs. MySQL vs. OushuDB vs. Trafodion

System Properties Comparison FoundationDB vs. Lovefield vs. MySQL vs. OushuDB vs. Trafodion

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

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

Description

Ordered key-value store. Core features are complimented by layers.

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Website

github.com/apple/foundationdb

google.github.io/lovefield

www.mysql.com

www.oushu.com/product/oushuDB

trafodion.apache.org

Technical documentation

apple.github.io/foundationdb

github.com/google/lovefield/blob/master/docs/spec_index.md

dev.mysql.com/doc

www.oushu.com/documentation

trafodion.apache.org/documentation.html

Developer

FoundationDB

Google

Oracle

since 2010, originally MySQL AB, then Sun

Oushu

Apache Software Foundation, originally developed by HP

Initial release

2013

2014

1995

2014

Current release

6.2.28, November 2020

2.1.12, February 2017

8.4.0, April 2024

4.0.1, August 2020

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++

JavaScript

C and C++

C++, Java

Server operating systems

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

some layers support typing

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

SQL

Support of SQL

supported in specific SQL layer only

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

Full-featured ANSI SQL support

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

JavaScript

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

C
C++

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

in SQL-layer only

yes

proprietary syntax

yes

Java Stored Procedures

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Kerberos, SSL and role based access

fine grained access rights according to SQL-standard

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