What is the correct way to structure this kind of data in Firestore?

I have seen videos and read the documentation of Cloud firestore, from Google Firebase service, but I can't figure this out coming from realtime database.

I have this web app in mind in which I want to store my providers from different category of products. I want perform a search query through all my products to find what providers I have for such product, and eventually access that provider info.

I am planning to use this structure for this purpose:

Providers ( Collection )
   Provider 1 ( Document )
      Name
      City
      Categories
   Provider 2
      Name
      City

Products ( Collection )
   Product 1 ( Document )
      Name
      Description
      Category
      Provider ID
   Product 2
      Name
      Description
      Category
      Provider ID

So my question is, is this approach the right way to access the provider info once I get the product I want?

I know this is possible in the realtime database, using the provider ID I could search for that provider in the providers section, but with Firestore I am not sure if its possible or if this is right approach.

Solution 1:

What is the correct way to structure this kind of data in Firestore?

You need to know that there is no "perfect", "the best" or "the correct" solution for structuring a Cloud Firestore database. The best and correct solution is the solution that fits your needs and makes your job easier. Bear also in mind that there is also no single "correct data structure" in the world of NoSQL databases. All data is modeled to allow the use-cases that your app requires. This means that what works for one app, may be insufficient for another app. So there is not a correct solution for everyone. An effective structure for a NoSQL type database is entirely dependent on how you intend to query it.

The way you are structuring your data looks good to me. In general, there are two ways in which you can achieve the same thing. The first one would be to keep a reference of the provider in the product object (as you already do) or to copy the entire provider object within the product document. This last technique is called denormalization and is a quite common practice when it comes to Firebase. So we often duplicate data in NoSQL databases, to suit queries that may not be possible otherwise. For a better understanding, I recommend you see this video, Denormalization is normal with the Firebase Database. It's for Firebase Realtime Database but the same principles apply to Cloud Firestore.

Also, when you are duplicating data, there is one thing that needs to keep in mind. In the same way, you are adding data, you need to maintain it. In other words, if you want to update/delete a provider object, you need to do it in every place that it exists.

You might wonder now, which technique is best. In a very general sense, the best way in which you can store references or duplicate data in a NoSQL database is completely dependent on your project's requirements.

So you should ask yourself some questions about the data you want to duplicate or simply keep it as references:

1. Is the static or will it change over time?
2. If it does, do you need to update every duplicated instance of the data so they all stay in sync? This is what I have also mentioned earlier.
3. When it comes to Firestore, are you optimizing for performance or cost?

If your duplicated data needs to change and stay in sync in the same time, then you might have a hard time in the future keeping all those duplicates up to date. This will also might imply you spend a lot of money keeping all those documents fresh, as it will require a read and write for each document for each change. In this case, holding only references will be the winning variant.

In this kind of approach, you write very little duplicated data (pretty much just the Provider ID). So that means that your code for writing this data is going to be quite simple and quite fast. But when reading the data, you will need to load the data from both collections, which means an extra database call. This typically isn't a big performance issue for reasonable numbers of documents, but definitely does require more code and more API calls.

If you need your queries to be very fast, you may want to prefer to duplicate more data so that the client only has to read one document per item queried, rather than multiple documents. But you may also be able to depend on local client caches makes this cheaper, depending on the data the client has to read.

In this approach, you duplicate all data for a provider for each product document. This means that the code to write this data is more complex, and you're definitely storing more data, one more provider object for each product document. And you'll need to figure out if and how to keep up to date on each document. But on the other hand, reading a product document now gives you all information about the provider document in one read.

This is a common consideration in NoSQL databases: you'll often have to consider write performance and disk storage vs. reading performance and scalability.

For your choice of whether or not to duplicate some data, it is highly dependent on your data and its characteristics. You will have to think that through on a case-by-case basis.

So in the end, remember that both are valid approaches, and neither of them is pertinently better than the other. It all depends on what your use-cases are and how comfortable you are with this new technique of duplicating data. Data duplication is the key to faster reads, not just in Cloud Firestore or Firebase Realtime Database but in general. Any time you add the same data to a different location, you're duplicating data in favor of faster read performance. Unfortunately in return, you have a more complex update and higher storage/memory usage. But you need to note that extra calls in Firebase real-time database, are not expensive, in Firestore are. How much duplication data versus extra database calls is optimal for you, depends on your needs and your willingness to let go of the "Single Point of Definition mindset", which can be called very subjective.

After finishing a few Firebase projects, I find that my reading code gets drastically simpler if I duplicate data. But of course, the writing code gets more complex at the same time. It's a trade-off between these two and your needs that determines the optimal solution for your app. Furthermore, to be even more precise you can also measure what is happening in your app using the existing tools and decide accordingly. I know that is not a concrete recommendation but that's software development. Everything is about measuring things.

Remember also, that some database structures are easier to be protected with some security rules. So try to find a schema that can be easily secured using Cloud Firestore Security Rules.

Please also take a look at my answer from this post where I have explained more about collections, maps and arrays in Firestore.