Christoph, Of course storage is not a problem. But, unnecessary data in a database in quantity can quickly become an indexing problem.
Here’s example for a device that store a lot of entities data in HA database :
112469|sensor|sensor.0x5c0272fffeceb025_humidity|47|{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "unit_of_measurement": "%", "friendly_name": "0x5c0272fffeceb025 humidity", "device_class": "humidity"}|119774|2021-02-02 18:05:35.071923|2021-02-02 20:46:59.554933|2021-02-02 20:46:59.554933|112457
112470|sensor|sensor.0x5c0272fffeceb025_melody|18|{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "friendly_name": "0x5c0272fffeceb025 melody"}|119775|2021-02-02 16:46:29.295481|2021-02-02 20:46:59.555115|2021-02-02 20:46:59.555115|112458
112471|sensor|sensor.0x5c0272fffeceb025_duration||{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "unit_of_measurement": "second", "friendly_name": "0x5c0272fffeceb025 duration"}|119776|2021-02-02 16:46:29.295626|2021-02-02 20:46:59.555276|2021-02-02 20:46:59.555276|112459
112472|sensor|sensor.0x5c0272fffeceb025_temperature_min||{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "unit_of_measurement": "\u00b0C", "friendly_name": "0x5c0272fffeceb025 temperature min"}|119777|2021-02-02 16:46:29.295767|2021-02-02 20:46:59.555469|2021-02-02 20:46:59.555469|112460
112473|sensor|sensor.0x5c0272fffeceb025_temperature_max||{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "unit_of_measurement": "\u00b0C", "friendly_name": "0x5c0272fffeceb025 temperature max"}|119778|2021-02-02 16:46:29.295904|2021-02-02 20:46:59.555626|2021-02-02 20:46:59.555626|112461
112474|sensor|sensor.0x5c0272fffeceb025_humidity_min||{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "unit_of_measurement": "%", "friendly_name": "0x5c0272fffeceb025 humidity min"}|119779|2021-02-02 16:46:29.296047|2021-02-02 20:46:59.555779|2021-02-02 20:46:59.555779|112462
112475|sensor|sensor.0x5c0272fffeceb025_humidity_max||{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "unit_of_measurement": "%", "friendly_name": "0x5c0272fffeceb025 humidity max"}|119780|2021-02-02 16:46:29.296184|2021-02-02 20:46:59.555930|2021-02-02 20:46:59.555930|112463
112476|sensor|sensor.0x5c0272fffeceb025_volume|low|{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "friendly_name": "0x5c0272fffeceb025 volume"}|119781|2021-02-02 16:46:29.296317|2021-02-02 20:46:59.556082|2021-02-02 20:46:59.556082|112464
112477|sensor|sensor.0x5c0272fffeceb025_linkquality|195|{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "unit_of_measurement": "lqi", "friendly_name": "0x5c0272fffeceb025 linkquality", "icon": "mdi:signal"}|119782|2021-02-02 20:43:12.334374|2021-02-02 20:46:59.556234|2021-02-02 20:46:59.556234|112465
112478|binary_sensor|binary_sensor.0x5c0272fffeceb025_humidity_alarm|off|{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "friendly_name": "0x5c0272fffeceb025 humidity alarm"}|119783|2021-02-02 16:45:56.557486|2021-02-02 20:46:59.556395|2021-02-02 20:46:59.556395|112466
112479|binary_sensor|binary_sensor.0x5c0272fffeceb025_temperature_alarm|off|{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "friendly_name": "0x5c0272fffeceb025 temperature alarm"}|119784|2021-02-02 16:45:56.557535|2021-02-02 20:46:59.556548|2021-02-02 20:46:59.556548|112467
112480|binary_sensor|binary_sensor.0x5c0272fffeceb025_alarm|off|{"alarm": false, "humidity": 47, "linkquality": 195, "melody": 18, "temperature": "18.3", "volume": "low", "friendly_name": "0x5c0272fffeceb025 alarm"}|119785|2021-02-02 16:45:56.557583|2021-02-02 20:46:59.556700|2021-02-02 20:46:59.556700|112468
We end up with 60 unnecessary data by queries batch. On few records is not problematic. On thousands of recordings, I hardly dare imagine it.
When I open Chronograf to explore my HA InfluxDB database, I have pain in my eyes
It would have been nice to be able to select which attributes to consider after discovery process.