DBMS > FoundationDB vs. GeoMesa vs. LeanXcale vs. MonetDB vs. Postgres-XL

System Properties Comparison FoundationDB vs. GeoMesa vs. LeanXcale vs. MonetDB 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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A relational database management system that stores data in columns

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

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Spatial DBMS

Key-value store
Relational DBMS

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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

github.com/apple/foundationdb

Technical documentation

apple.github.io/foundationdb

www.geomesa.org/documentation/stable/user/index.html

www.monetdb.org/Documentation

www.postgres-xl.org/documentation

Developer

FoundationDB

CCRi and others

LeanXcale

MonetDB BV

Initial release

2013

2014

2015

2004

2014

since 2012, originally named StormDB

Current release

6.2.28, November 2020

5.0.0, May 2024

Dec2023 (11.49), December 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

commercial

Open Source

Mozilla Public License 2.0

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++

Scala

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

supported in specific SQL layer only

yes

through Apache Derby

yes

SQL 2003 with some extensions

yes

distributed, parallel query execution

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

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

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
Java
Scala

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

Server-side scripts

Stored procedures

in SQL-layer only

yes, in SQL, C, R

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding via remote tables

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

depending on storage layer

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

MVCC

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.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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