This article uses venv, but you can use conda, pipenv or pyenv as well.įinally, some experience with Flux querying. Setting up InfluxDB with Pythonīefore getting started, make sure you have Python 3.6 or later installed on your computer. It has a free open source version you can run locally, and there’s a cloud version that supports major cloud services such as AWS, GCP and Azure. And let’s not forget that it outperforms Elasticsearch and Cassandra. InfluxDB comes with a pre-built dashboard where you can analyze your time series data without much groundwork. The platform handles the massive volume of time-stamped data produced by IoT devices, apps, networks and containers. InfluxData, creator of the open source time-series platform InfluxDB, empowers developers to build transformative monitoring, analytics and IoT applications quicker and to scale. GETTING STARTED WITH PYTHON ON MAC CODEYou can access all the code written in this tutorial in this repo. GETTING STARTED WITH PYTHON ON MAC HOW TOThis article will show you how to set up InfluxDB using Python, working with stock data fetched using the Yahoo Finance API. InfluxDB has created an open source time-series database that makes it easier for developers to work with time-series data. ![]() ![]() Tracking an athlete’s vitals and performance during a game.Tracking power usage in IoT devices such as a smart power grid.Monitoring the sensor data from a car or a plane for safety purposes.Monitoring the logs and metrics of an API or web service.Analyzing financial trends in stock prices.This is particularly useful in situations like: ![]() Querying or performing aggregation on this data also leads to performance issues when using relational databases.Ī time-series database (TSDB), on the other hand, is optimized to store time-series data points. If you want to store data that changes every minute (that’s more than half a million data points a year!) from potentially thousands of different sensors, servers, containers, or devices, you’re inevitably going to run into scalability issues. Rahul Banerjee is a computer engineering student who likes playing around with different libraries/APIs.Īlthough time-series data can be stored in a MySQL or PostgreSQL database, that’s not particularly efficient.
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