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InfluxDB

An open-source distributed time series database with no external dependencies

What is InfluxDB?

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.
InfluxDB is a tool in the Databases category of a tech stack.
InfluxDB is an open source tool with 22.4K GitHub stars and 3.1K GitHub forks. Here’s a link to InfluxDB's open source repository on GitHub

Who uses InfluxDB?

Companies
229 companies reportedly use InfluxDB in their tech stacks, including GO-JEK, Hepsiburada, and deleokorea.

Developers
616 developers on StackShare have stated that they use InfluxDB.

InfluxDB Integrations

Grafana, Traefik, Redash, Sensu, and k6 are some of the popular tools that integrate with InfluxDB. Here's a list of all 19 tools that integrate with InfluxDB.
Pros of InfluxDB
51
Time-series data analysis
28
Easy setup, no dependencies
24
Fast, scalable & open source
21
Open source
18
Real-time analytics
6
Continuous Query support
5
Easy Query Language
4
HTTP API
4
Out-of-the-box, automatic Retention Policy
1
Offers Enterprise version
1
Free Open Source version
Decisions about InfluxDB

Here are some stack decisions, common use cases and reviews by companies and developers who chose InfluxDB in their tech stack.

Shared insights
on
InfluxDBInfluxDBJSONJSON

Hi all, I am trying to decide on a database for time-series data. The data could be tracking some simple series like statistics over time or could be a nested JSON (multi-level nested). I have been experimenting with InfluxDB for the former case of a simple list of variables over time. The continuous queries are powerful too. But for the latter case, where InfluxDB requires to flatten out a nested JSON before saving it into the database the complexity arises. The nested JSON could be objects or a list of objects and objects under objects in which a complete flattening doesn't leave the data in a state for the queries I'm thinking.

[ 
  { "timestamp": "2021-09-06T12:51:00Z",
    "name": "Name1",
    "books": [
        { "title": "Book1", "page": 100 },
        { "title": "Book2", "page": 280 },
    ]
  },
 { "timestamp": "2021-09-06T12:52:00Z",
   "name": "Name2",
   "books": [
       { "title": "Book1", "page": 320},
       { "title": "Book2", "page": 530 },
       { "title": "Book3", "page": 150 },
   ]
 }
]

Sample query: With a time range, for name xyz, find all the book title for which # of page < 400.

If I flatten it completely, it will result in fields like books_0_title, books_0_page, books_1_title, books_1_page, ... And by losing the nested context it will be hard to return one field (title) where some condition for another field (page) satisfies.

Appreciate any suggestions. Even a piece of generic advice on handling the time-series and choosing the database is welcome!

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Muhammad Asif Azam
Software Develpor (ioT) at Vappar · | 2 upvotes · 4K views
Shared insights
on
ReactReactInfluxDBInfluxDBPythonPython

I am facing a problem of a high latency rate. How can I make it real-time?

My stack is Python (reading some data from serial), InfluxDB (Data Store in DB) React (Front-end show data on a web app with API)

The cycle is Read Data, Store, and then Show Front-end data from API(DB).

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Hi everyone. I'm trying to create my personal syslog monitoring.

  1. To get the logs, I have uncertainty to choose the way: 1.1 Use Logstash like a TCP server. 1.2 Implement a Go TCP server.

  2. To store and plot data. 2.1 Use Elasticsearch tools. 2.2 Use InfluxDB and Grafana.

I would like to know... Which is a cheaper and scalable solution?

Or even if there is a better way to do it.

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Blog Posts

InfluxDB's Features

  • Time-Centric Functions
  • Scalable Metrics
  • Events
  • Native HTTP API
  • Powerful Query Language
  • Built-in Explorer

InfluxDB Alternatives & Comparisons

What are some alternatives to InfluxDB?
TimescaleDB
TimescaleDB: An open-source database built for analyzing time-series data with the power and convenience of SQL — on premise, at the edge, or in the cloud.
Redis
Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Prometheus
Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
See all alternatives

InfluxDB's Followers
901 developers follow InfluxDB to keep up with related blogs and decisions.