DBMS > FoundationDB vs. MySQL vs. Teradata vs. Trino

System Properties Comparison FoundationDB vs. MySQL vs. Teradata vs. Trino

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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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.

Description

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

Widely used open source RDBMS

A hybrid cloud data analytics software platform (Teradata Vantage)

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

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

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

github.com/apple/foundationdb

www.mysql.com

www.teradata.com

trino.io

Technical documentation

apple.github.io/foundationdb

dev.mysql.com/doc

docs.teradata.com

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

FoundationDB

Oracle

since 2010, originally MySQL AB, then Sun

Teradata

Trino Software Foundation

Initial release

2013

1995

1984

2012

2020 rebranded from PrestoSQL

Current release

6.2.28, November 2020

8.4.0, April 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache Version 2.0

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 and C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

hosted
Linux

Linux
macOS

for devlopment

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

depending on connected data-source

SQL

Support of SQL

supported in specific SQL layer only

yes

with proprietary extensions

yes

SQL 2016 + extensions

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

in SQL-layer only

yes

proprietary syntax

yes

UDFs, stored procedures, table functions in parallel

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Hashing

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

depending on connected data-source

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

depending on connected data-source

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

depending on connected data-source

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 with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
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Key customers

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Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

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