DBMS > Apache Drill vs. Citus vs. FoundationDB vs. MaxDB vs. Postgres-XL

System Properties Comparison Apache Drill vs. Citus vs. FoundationDB vs. MaxDB vs. Postgres-XL

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

A robust and reliable RDBMS optimized to run all major SAP solutions

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	2.15
Rank	#123	Overall
	#60	Relational DBMS

Score	1.07
Rank	#188	Overall
	#31	Document stores
	#28	Key-value stores
	#86	Relational DBMS

Score	2.65
Rank	#111	Overall
	#55	Relational DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Website

drill.apache.org

www.citusdata.com

github.com/apple/foundationdb

maxdb.sap.com

www.postgres-xl.org

Technical documentation

drill.apache.org/docs

docs.citusdata.com

apple.github.io/foundationdb

maxdb.sap.com/documentation

www.postgres-xl.org/documentation

Developer

Apache Software Foundation

FoundationDB

SAP, acquired from Software AG (Adabas-D) in 1997

Initial release

2012

2010

2013

1984

2014

since 2012, originally named StormDB

Current release

1.20.3, January 2023

8.1, December 2018

6.2.28, November 2020

7.9.10.12, February 2024

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL, commercial license also available

Open Source

Apache 2.0

commercial

Limited community edition free

Open Source

Mozilla public license

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

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

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

specific XML type available, but no XML query functionality

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

standard, with numerous extensions

supported in specific SQL layer only

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

ADO.NET
JDBC
ODBC
WebDAV

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

Supported programming languages

C++

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
C#
Java
Perl
PHP
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

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

in SQL-layer only

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

in SQL-layer only

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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