Hey, curious how scalable the platform is?
I rate that it’s hosted on AWS and performance has been great so far, but would be good to know if there are any general guidelines that things will start slowing down at.
In particular I’m interested in timeseries data, say a table with schema user_id, event_id, timestamp, lat, lng
This could get a lot of rows pretty quickly, so curious whether 8base will be able to handle it or you’d recommend storing this on another platform?
On a related note, what can be learned and applied from AWS’s guides?
In the business plan, is any reporting or metrics available?
What about using graphql benchmarking tools?
hey @samwoolertonLW - there really isn’t any limitation in this regard. 8base will maximize the read/write capacity of your database as requests come in, and lambda is able to handle extremely high traffic. There really aren’t any guidelines, as everything will scale pretty seamlessly.
Regarding time-series data, 8base will easily be able to handle that, it’s just going to generate a lot of rows and API requests!
To help minimize the api requests, I’d be pretty specific in what the optimal time interval is between records, as well as the batch mutations with a createMany operation. That way, maybe you persist every 20 records and improve your performance.
Something like.
mutation {
userUpdate(data: {
id: "ixhieuygx08w360836x",
movements: {
create: [
{ timestamp: "01-02-2019T0.002939", lat/lng },
{ timestamp: "01-02-2019T0.002939", lat/lng },
{ timestamp: "01-02-2019T0.002939", lat/lng }
# 17 more or however many...
]
}
})
{
movements {
count
}
}
}