DBMS > Faircom DB vs. Graph Engine vs. Percona Server for MongoDB vs. RethinkDB

System Properties Comparison Faircom DB vs. Graph Engine vs. Percona Server for MongoDB vs. RethinkDB

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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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Key-value store
Relational DBMS

Graph DBMS
Key-value store

Document store

Secondary database models

Spatial DBMS

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

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.50
Rank	#250	Overall
	#39	Document stores

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

www.faircom.com/products/faircom-db

www.graphengine.io

www.percona.com/mongodb/software/percona-server-for-mongodb

rethinkdb.com

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

www.graphengine.io/docs/manual

docs.percona.com/percona-distribution-for-mongodb

rethinkdb.com/docs

Developer

FairCom Corporation

Microsoft

Percona

The Linux Foundation

since July 2017

Initial release

1979

2010

2015

2009

Current release

V13, July 2024

3.4.10-2.10, November 2017

2.4.1, August 2020

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

MIT License

Open Source

GPL Version 2

Open Source

Apache Version 2

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

ANSI C, C++

.NET and C

C++

Server operating systems

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

easily portable to other OSs

.NET

Linux

Linux
OS X
Windows

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

string, binary, float, bool, date, geometry

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

APIs and other access methods

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

RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

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

C#
C++
F#
Visual Basic

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

JavaScript

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

horizontal partitioning

Sharding

range based

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).

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

via In-Memory Engine

User concepts

Access control

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

Access rights for users and roles

yes

users and table-level permissions

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More resources

DB-Engines blog posts

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4 August 2014, Paul Andlinger

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