DBMS > 4D vs. InfluxDB vs. KeyDB vs. Memcached vs. MongoDB

System Properties Comparison 4D vs. InfluxDB vs. KeyDB vs. Memcached vs. MongoDB

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

DBMS for storing time series, events and metrics

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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	2.68
Rank	#110	Overall
	#54	Relational DBMS

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.80
Rank	#219	Overall
	#31	Key-value stores

Score	20.74
Rank	#32	Overall
	#4	Key-value stores

Score	423.96
Rank	#5	Overall
	#1	Document stores

Website

www.4d.com

www.influxdata.com/products/influxdb-overview

github.com/Snapchat/KeyDB
keydb.dev

www.memcached.org

www.mongodb.com

Technical documentation

developer.4d.com

docs.influxdata.com/influxdb

docs.keydb.dev

github.com/memcached/memcached/wiki

www.mongodb.com/docs/manual

Developer

4D, Inc

EQ Alpha Technology Ltd.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

MongoDB, Inc

Initial release

1984

2013

2019

2003

2009

Current release

v20, April 2023

2.7.5, January 2024

1.6.25, March 2024

6.0.7, June 2023

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD-3

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.

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: 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++

Server operating systems

OS X
Windows

Linux
OS X

through Homebrew

Linux

FreeBSD
Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

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

Numeric data and Strings

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

HTTP API
JSON over UDP

Proprietary protocol

RESP - REdis Serialization Protoco

Proprietary protocol

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

4D proprietary IDE
PHP

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

.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
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

yes

Lua

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

Sharding

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.

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

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

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Depending on used storage engine

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Users and groups

simple rights management via user accounts

simple password-based access control and ACL

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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News

Sync Data from InfluxDB v2 to v3 With the Quix Template
8 April 2024

Infrastructure Monitoring Basics: Getting Started with Telegraf, InfluxDB, and Grafana
5 April 2024

Comparing Dates in Java: A Tutorial
3 April 2024

Python ARIMA Tutorial
29 March 2024

Time Series, InfluxDB, and Vector Databases
26 March 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.