DBMS > Apache Druid vs. FoundationDB vs. PostgreSQL vs. ToroDB

System Properties Comparison Apache Druid vs. FoundationDB vs. PostgreSQL vs. ToroDB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS
Time Series DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Document store

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

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

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

druid.apache.org

github.com/apple/foundationdb

www.postgresql.org

github.com/torodb/server

Technical documentation

druid.apache.org/docs/latest/design

apple.github.io/foundationdb

www.postgresql.org/docs

Developer

Apache Software Foundation and contributors

FoundationDB

PostgreSQL Global Development Group

www.postgresql.org/developer

8Kdata

Initial release

2012

2013

1989

1989: Postgres, 1996: PostgreSQL

2016

Current release

29.0.1, April 2024

6.2.28, November 2020

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

BSD

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-less columns are supported

schema-free

some layers support schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

some layers support typing

yes

string, integer, double, boolean, date, object_id

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

supported in specific SQL layer only

yes

standard with numerous extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

in SQL-layer only

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Access rights for users and roles

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