A weather station on a Raspberry Pi is one of the projects that pays back every day. Fifteen dollars of BME280 sensor and an SDR dongle is enough to catch every 433 MHz weather station in a two-block radius, and the Pi has plenty of headroom to turn all of that into a rain alert on the phone. The apps make the difference between “cool graph” and “actually useful”. These seven apps for a Raspberry Pi weather station in 2026 are the ones that keep the project running past the first week.
What to look for in a Raspberry Pi weather station stack
Weather projects tend to accumulate parts. A few questions keep the stack from becoming a mess:
- Where does the data come from? Local sensors on GPIO, a bought station via USB or 433 MHz, an online API, or all three?
- Where does it live? A local time-series database, a hosted service, or straight into Home Assistant?
- Who sees it? A wall dashboard, a phone notification, both?
- What happens when it rains? A push notification, a light that turns red, a text to a phone that is not home?
- How much does it drift? Cheap sensors are cheap. Calibration and outlier filtering matter.
The apps below split responsibility for those questions.
The apps
1. Home Assistant, best hub for reacting to the data
Home Assistant is where the weather station goes from “reads sensors” to “sends me a rain alert before I leave for work”. Its Weather template makes local sensors, MQTT topics, and online forecasts look the same. Automations trigger notifications, lights, or scripts on any of them.
Where it falls short: it is a full smart-home stack. If you only want a graph, this is more than you need.
Pricing:
- Free: Home Assistant Core, Container, Supervised, and OS
- Paid: Nabu Casa Cloud is optional
- Best if: you already run Home Assistant or want to
Bottom line: the pick that turns weather data into decisions.
2. Weewx, best for a purpose-built weather stack
Weewx is a Python weather-station engine that predates most of the smart-home era. It talks to dozens of commercial stations directly, keeps its own database, and generates the classic weather dashboard with graphs and historical records. Running on a Pi, it is the “Grandma had one of these” of weather software.
Where it falls short: the built-in HTML dashboard looks its age. Extensions cover most needs, but they need setup.
Pricing:
- Free: fully open source
- Paid: none
- Best if: you own a Davis, Fine Offset, or Ambient Weather station
Bottom line: the pick when the source is a commercial station and you want a purpose-built system.
3. Rtl_433, best for pulling in every wireless sensor within range
Rtl_433 is a decoder that pairs a cheap RTL-SDR dongle on the Pi with the 433 MHz stream of every weather sensor, tire-pressure gauge, and smart-home sensor for streets around. It publishes each decoded reading to MQTT, where the rest of the stack picks it up.
Where it falls short: the antenna makes a bigger difference than the SDR does. Some readings need filtering to sort your own sensor from the neighbor’s.
Pricing:
- Free: fully open source
- Paid: none, though the SDR dongle is a small hardware cost
- Best if: you want to pull in weather data without buying a station
Bottom line: the pick that gets you weather sensors without owning weather sensors.
4. Node-RED, best for logic between sensors and actions
Node-RED is the flow editor that connects “sensor changed” to “do something”. Its node library covers MQTT, HTTP, weather APIs, and Home Assistant entities. For projects that outgrow a simple template, Node-RED is what turns a set of sensor readings into a decision.
Where it falls short: the visual flow editor is love or hate. Complex flows benefit from careful naming or they become a wire ball.
Pricing:
- Free: fully open source
- Paid: none
- Best if: your Pi is doing more than one thing with the weather data
Bottom line: the pick when the rules got complicated.
5. Grafana, best for a serious dashboard
Grafana builds the dashboard everyone shares screenshots of. Point it at InfluxDB or your Home Assistant recorder and you get proper graphs, alert rules, and a wall panel worth mounting. On a Pi 5 it runs comfortably; on a Pi 4 it is fine for one browser tab.
Where it falls short: the initial learning curve is real. Not the pick when a Home Assistant dashboard already does the job.
Pricing:
- Free: Grafana OSS
- Paid: Grafana Cloud has a generous free tier for hobbyists
- Best if: you want a dashboard that goes on the wall
Bottom line: the pick when the graphs are the point.
6. InfluxDB, best time-series database for the graphs
InfluxDB is the storage half of the classic weather-Pi stack. Time-series data compresses well, queries are fast, and Grafana talks to it natively. Point Node-RED or Home Assistant at it and forget it.
Where it falls short: InfluxDB 2.x has a steeper learning curve than 1.x had. Backups need a plan.
Pricing:
- Free: InfluxDB OSS
- Paid: InfluxDB Cloud tier for hosted storage
- Best if: you want more than a few weeks of history
Bottom line: the pick for a Pi that keeps years of weather data.
7. MQTT Explorer, best for debugging the pipeline
MQTT Explorer is the desktop app that saves the day when the weather-Pi’s data does not show up where it should. Point it at the Mosquitto broker on the Pi and every message from Rtl_433, Home Assistant, and Node-RED becomes visible in a proper tree view.
Where it falls short: it is a debugger. The Pi runs fine without it; you install it when something breaks.
Pricing:
- Free: the core app
- Paid: MQTT Explorer Pro one-time license for advanced features
- Best if: you spend any time wondering why a sensor stopped updating
Bottom line: the pick for the day you need to see what is on the wire.
How to pick the right stack
Start with Home Assistant and one BME280 sensor. That is enough for a rain alert. Add Rtl_433 with an RTL-SDR when you want to pull in nearby wireless sensors. Add Node-RED when the automations grow past a few triggers. Add InfluxDB and Grafana together when you want long-term charts on the wall. Add Weewx if you buy a proper commercial weather station and want the classic weather-dashboard experience. Install MQTT Explorer on your laptop the first time something breaks. Skip the whole stack if a phone app already tells you what you needed to know.
FAQ
Do I need a Raspberry Pi 5 for this? No. A Pi 4 with 4 GB of RAM runs Home Assistant, Rtl_433, Node-RED, InfluxDB, and Grafana together. A Pi 5 is smoother but not required.
Which sensor should I start with? A BME280 or BME680 breakout is the standard first sensor. It covers temperature, humidity, and pressure over I2C for about 15 dollars.
Can I catch my neighbor’s weather station? Rtl_433 with a decent 433 MHz antenna will decode Acurite, La Crosse, Fine Offset, and Ambient Weather stations within a couple of hundred meters. The legality of using data from someone else’s station varies by region; treat neighbor stations as reference points, not primary data.
How much power does this use? A Raspberry Pi 4 with an SDR dongle uses about 5 to 7 watts. A Pi 5 uses about 8 to 10.
Do I need Grafana if I already use Home Assistant dashboards? No. Grafana wins when you want a wall panel or long-term charts; Home Assistant’s built-in dashboards cover most day-to-day needs.
