It is frankly not very affordable for a bootstrapped startup.
My questions are how easy is it to host this thing. (It would be perfect if someone makes a deploy to heroku button so that we can just do this in one click)
It is frankly not very affordable for a bootstrapped startup.
My questions are how easy is it to host this thing. (It would be perfect if someone makes a deploy to heroku button so that we can just do this in one click)
That's not true at all.
SaaS companies are valued on recurring revenue, lifetime value, retention and future cash flow. Number of users is almost irrelevant as long as those metrics are moving up and to the right to a healthy degree.
Chart.io has already changed their pricing once and I share your prediction that they will change it again: to charge even more. And grow further as a result.
SMBs are a tough market for SaaS companies with a product that has any complexity whatsoever, both in terms of usage and distribution.
Edit: what exactly are you wagering on?
Although this currently only let's you push metrics via the API or upload a CSV. I personally would not be comfortable having a 3th party connecting directly to my database.
The product is still in development but I would love to get some first feedback / user testing.
I initially thought the project was a subtitute for chart.io. However, it seems like the project is about "collect and visualize data".
It is not to visual data by connecting to your own database. Rather it allows you to import data from an mysql database
Here is an example that connects to a MySQL database on localhost: https://github.com/paulasmuth/fnordmetric/blob/master/fnordm...
Note that the IMPORT statement might be a bit misleading. The IMPORT statement only creates a "virtual table", it doesn't actually copy any data. As much of the query as possible is pushed down into MySQL/the external data source and the charts will be generated from the query result that is returned by the external data source.
FnordMetric aims to fix that by extending standard SQL; it allows you to express the data query and the chart specification in a coherent fashion (SQL).