DBMS > Memcached vs. MongoDB vs. Oracle Coherence

System Properties Comparison Memcached vs. MongoDB vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

In-memory key-value store, originally intended for caching

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

Oracles in-memory data grid solution

Primary database model

Key-value store

Document store

Key-value 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

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

Score	24.64
Rank	#33	Overall
	#4	Key-value stores

Score	477.66
Rank	#5	Overall
	#1	Document stores

Score	2.36
Rank	#119	Overall
	#23	Key-value stores

Website

www.memcached.org

www.mongodb.com

www.oracle.com/middleware/technologies/coherence.html

Technical documentation

github.com/memcached/memcached/wiki

docs.mongodb.com/manual

docs.oracle.com/en/middleware/standalone/coherence

Developer

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

MongoDB, Inc

Oracle

Initial release

2003

2009

2007

Current release

1.6.15, March 2022

6.0.0, July 2022

12c, September 2016

License

Commercial or Open Source

Open Source

BSD license

Open Source

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

commercial

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.

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MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

All OS with a Java VM

Data scheme

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.

schema-free

Typing

predefined data types such as float or date

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

Read-only SQL queries via the MongoDB Connector for BI

APIs and other access methods

Proprietary protocol

proprietary protocol using JSON

JCache
JPA
RESTful HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

.Net
C++
Java

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

in MongoDB Atlas only

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

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.

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

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

yes, with selectable consistency level

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

can be individually decided for each write operation

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

optionally

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

yes

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users and roles

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

Specific characteristics

MongoDB’s application data platform provides developers a unified interface to power...
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Competitive advantages

The MongoDB platform can be used by developers building transactional, operational,...
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Typical application scenarios

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

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

200+ million downloads, over 1.5M Atlas database clusters under management handling...
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Licensing and pricing models

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