DBMS > Apache Drill vs. Apache Phoenix vs. Faircom EDGE vs. FoundationDB vs. MongoDB

System Properties Comparison Apache Drill vs. Apache Phoenix vs. Faircom EDGE vs. FoundationDB vs. MongoDB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

A scale-out RDBMS with evolutionary schema built on Apache HBase

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

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	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Score	0.97
Rank	#191	Overall
	#32	Document stores
	#28	Key-value stores
	#87	Relational DBMS

Score	410.24
Rank	#5	Overall
	#1	Document stores

Website

drill.apache.org

phoenix.apache.org

www.faircom.com/products/faircom-edge

github.com/apple/foundationdb

www.mongodb.com

Technical documentation

drill.apache.org/docs

phoenix.apache.org

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

apple.github.io/foundationdb

www.mongodb.com/docs/manual

Developer

Apache Software Foundation

FairCom Corporation

FoundationDB

MongoDB, Inc

Initial release

2012

2014

1979

2013

2009

Current release

1.20.3, January 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

V3, October 2020

6.2.28, November 2020

7.0.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Restricted, free version available

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

Java

ANSI C, C++

C++

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

late-bound, schema-on-read capabilities

Flexible Schema (defined schema, partial schema, schema free)

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

yes

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

ANSI SQL queries

supported in specific SQL layer only

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

C++

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

.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

user defined functions

yes

.Net, JavaScript, C/C++

in SQL-layer only

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

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

Multi-source replication
Source-replica replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency

Immediate Consistency
Tunable Consistency

Linearizable consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

when using SQL

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

across SQL and NoSQL

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

optional, enabled by default

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

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Depending on the underlying data source

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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