DBMS > InfluxDB vs. MongoDB vs. TimescaleDB

System Properties Comparison InfluxDB vs. MongoDB vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

DBMS for storing time series, events and metrics

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Time Series DBMS

Document store

Time Series DBMS

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

Relational DBMS

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

Score	21.78
Rank	#28	Overall
	#1	Time Series DBMS

Score	402.51
Rank	#5	Overall
	#1	Document stores

Score	3.59
Rank	#72	Overall
	#5	Time Series DBMS

Website

www.influxdata.com/products/influxdb-overview

www.mongodb.com

www.timescale.com

Technical documentation

docs.influxdata.com/influxdb

www.mongodb.com/docs/manual

docs.timescale.com

Developer

MongoDB, Inc

Timescale

Initial release

2013

2009

2017

Current release

2.7.6, April 2024

7.0.5, January 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

MIT-License; commercial enterprise 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.

Implementation language

C++

Server operating systems

Linux
OS X

through Homebrew

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

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.

yes

Typing

predefined data types such as float or date

Numeric data and Strings

yes

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

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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-like query language

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP API
JSON over UDP

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

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.

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

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

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

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

simple rights management via user accounts

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

News

5 Must-Have Python Plugins for InfluxDB 3 Core & Enterprise
13 May 2025

Hack to the Future: InfluxDB 3 Hackathon
5 May 2025

Building Smarter Manufacturing Systems with Bosch Rexroth and InfluxDB
23 April 2025

Build a Time Series Forecasting Pipeline in InfluxDB 3 Without Writing Code
17 April 2025

InfluxDB 3 Core & Enterprise GA: The Next Generation Time Series Platform for Developers is Here
15 April 2025

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