Firebase - Perform Analytics from database/firestore data

Question

I am using Firebase as my authentication and database platform in my React Native-Expo app. I have not yet decided if I will be using the realtime-database or Firestore database.

I need to perform statistical analysis on daily data gathered from my users, which is stored in the database. I.e. the users type in their daily intake of protein, from it I would like to calculate their weekly average, expected monthly average, provide suggestions of types of food if protein intake is too low and etc.

What would be the best approach in order to achieve the result wanted in my specific situation?

I am really unfamiliar and stepping into uncharted territory regarding on how I can accomplish this. I have read that Firebase Analytics generates different basic analytics regarding usage of the app, number crash-free users etc. But can it perform analytics on custom events? Can I create a custom event for Firebase analytics to keep track of a certain node in my database, and output analytics from that? And then of course, if yes, does it work with React Native-Expo or do I need to detach from Expo? In addition, I have read that Firebase Analytics can be combined with Google BigQuery. Would this be an alternative for my case?

Are there any other ways of performing such data analysis on my data stored in Firebase database? For example, export the data and use Python and SciKit Learn?

Whatever opinion or advice you may have, I would be grateful if you could share it!

Answer 1

You're not alone - many people building web apps on GCP have this question, and there is no single answer.

I'm not too familiar with Firebase Analytics, but can answer the question for Firestore and for your custom analytics (e.g. weekly avg protein consumption)

The first thing to point out is that Firestore, unlike other NoSQL databases, is storage only. You can't perform aggregations in real time like you can with MongoDB, so the calculations have to be done somewhere else.

The best practice recommended by GCP in this case is indeed to do a regular export of your Firestore data into BQ (BigQuery), and you can run analytical calculations there in the meantime. You could also, when a user inputs some data, send that to Pub/Sub and use one of GCP Dataflow's streaming templates to stream the data into BQ, and have everything in near real time.

Here's the issue with that however: while this solution gives you real time, and is very scalable, it gets expensive fast, and if you're more used to Python than SQL to run analytics it can be a steep learning curve. Here's an alternative I've used for smaller webapps, which scales well for <100k users and costs <$20 a month on GCP's current pricing:

1. Write a Python script that grabs the data from Firestore (using the Firestore Python SDK), generates the analytics you need on it, and writes the results back to a Firestore collection
2. Create an endpoint for that function using Flask or Django
3. Deploy that server application on Cloud Run, preventing unauthenticated invocations (you'll only be calling it from within GCP) - see this article, steps 1 and 2 only. You can also deploy the Python script(s) to GCP's Vertex AI or hosted Jupyter notebooks if you're more comfortable with that
4. Use Cloud Scheduler to call that function every x minutes - see these docs for authentication
5. Have your React app query the "analytics results" collection to get the results

Answer 2

My solution is a FlutterWeb based Dashboard that displays relevant data in (near) realtime like the Regular Flutter IOS/Android app and likewise some aggregated data.

The aggregated data is compiled using a few nodejs based triggers in the database that does any analytic lifting and hence is also near realtime. If you study pricing you will learn, that function invocations are pretty cheap unless of-course you happen to make a 'desphew' :)

Answer 3

I came up with a great solution.

I used the inbuilt firebase BigQuery plugin. Then I used Cube.js (deployed on GCP - cloud run on docker) on top of bigquery.

Cube.js just makes everything just so easy. You do need to make a manual query It tries to do optimize queries. On top of that, it uses caching so you won't get big bills on GCP. I think this is the best solution I was able to find. And this is infinitely scalable and totally real-time.

Also if you are a small startup then it is mostly free with GCP - free limits on cloud run and BigQuery.