DBMS > BigchainDB vs. FoundationDB vs. MongoDB

System Properties Comparison BigchainDB vs. FoundationDB vs. MongoDB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Document store

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	0.73
Rank	#215	Overall
	#35	Document stores

Score	0.89
Rank	#197	Overall
	#32	Document stores
	#29	Key-value stores
	#92	Relational DBMS

Score	402.51
Rank	#5	Overall
	#1	Document stores

Website

www.bigchaindb.com

github.com/apple/foundationdb

www.mongodb.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

apple.github.io/foundationdb

www.mongodb.com/docs/manual

Developer

FoundationDB

MongoDB, Inc

Initial release

2016

2013

2009

Current release

6.2.28, November 2020

7.0.5, January 2024

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Python

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

some layers support schemas

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

Typing

predefined data types such as float or date

some layers support typing

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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.

Secondary indexes

yes

SQL

Support of SQL

supported in specific SQL layer only

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

CLI Client
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Server-side scripts

Stored procedures

in SQL-layer only

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

in SQL-layer only

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

optional, enabled by default

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

yes

Access rights for users and roles

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