DBMS > Faircom DB vs. MongoDB vs. Spark SQL

System Properties Comparison Faircom DB vs. MongoDB vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Key-value store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Search engine

integrated Lucene index, currently in MongoDB Atlas only.

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

Score	0.52
Rank	#226	Overall
	#35	Key-value stores
	#111	Relational DBMS

Score	462.39
Rank	#5	Overall
	#1	Document stores

Score	19.46
Rank	#34	Overall
	#21	Relational DBMS

Website

www.faircom.com/products/faircom-db

www.mongodb.com

spark.apache.org/sql

Technical documentation

learn.faircomcorp.com/developers/documentation_directory

docs.mongodb.com/manual

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

FairCom Corporation

MongoDB, Inc

Apache Software Foundation

Initial release

1979

2009

2014

Current release

V12, November 2020

4.4.4 , February 2021

3.1.1, March 2021

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

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

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

MongoDB Atlas: the global and fully-managed cloud database service from the makers of MongoDB. Deploy across AWS, Azure, or GCP.
ScaleGrid for MongoDB: Fully managed hosting for MongoDB database on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.

Implementation language

ANSI C, C++

C++

Scala

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema free, schema optional, schema required, partial schema,

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.

yes

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

Read-only SQL queries via the MongoDB Connector for BI

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

proprietary protocol using JSON

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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
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

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

partitioned by hashed, ranged, or zoned sharding keys

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

tunable from ACID to Eventually Consistent

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

optional

yes

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

Fine grained access rights according to SQL-standard with additional protections for files

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Achieve Hundreds of Thousands of Transactions Per Second on A Single Database Server...
» more

MongoDB is the leading modern, general purpose data platform, designed to unleash...
» more

Competitive advantages

Top Features SQL Key-value store and navigational NoSQL API Indexed binary objects...
» more

The MongoDB platform can be used by developers building transactional, operational,...
» more

Typical application scenarios

Real-time transaction processing solutions leverage FairCom DB because its NoSQL...
» more

Internet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
» more

Key customers

Microsoft, UPS, Verizon, Motorola, Commvault, Thomson Reuters, ACI, BNY Mellon, Rockwell...
» more

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

From banking and financial transactions, transportation, warehouse automation, package...
» more

125 million downloads (growing at more than 30 thousand downloads per day), over...
» more

Licensing and pricing models

Just as the technical aspects of FairCom DB are flexible to meet operation requirements,...
» more

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.