I have a question regarding payment at the Cloud Firestore compared to the Realtime Database. At Firestore you pay per read/write per document, right? In other words: If I display a list of 1000 documents in a collection, do I pay for 1000 reads?
I have a few collections in my app with many (200-300) documents, which unfortunately all have to be displayed on one page. My app has about 10,000 active users. After the calculation I am definitely financially broke... :-)
Therefore my question: Are 300 elements also 300 reads taken into account if I save the 300 elements in ONE document as an Array and retrieve them? Is then only the one document calculated as a read? Or also the 300 elements from the created array?
If I display a list of 1000 documents in a collection, do I pay for 1000 reads?
You only pay for documents that are read on/from the server. Most Firestore SDKs implement a client-side cache, which may significantly reduce the number of documents that are read on/from the server.
I have a few collections in my app with many (200-300) documents, which unfortunately all have to be displayed on one page
One way to reduce the number of read operations is to model the data for that one page into a separate single document. This document is essentially the data for a single page in your app, meaning that you update it whenever any of the underlying data updates. That leads to more code when you write updates to the database, but it saves you 299 document reads for every user accessing the page.
Also see:
Cloud Firestore Pricing | Get to Know Cloud Firestore #3
Firestore: How are "reads" calculated for the quota?
Firebase firestore pricing for querying
Understanding Firestore Pricing
Related
I am using both Firebase Database and Firestore in my app. I store users data like name, email, uid etc small details in documents of a collection as Users in firestore. It works perfectly. I made a node as Friends in firebase database to store friends list of a user. So whenever user open the app, it calls his information from Users from firestore and also his friends list from Friends from firebase database.
Now the thing is by this way it calls data from the Firestore and the Firebase database. So it means they are 2 requests/reads, one to Friends node and other to a document from Users collection. I think it would be better if i store friends list in Users document as an Array. So i will get only 1 read in Firestore. But i think that when the arrays of his friends list increases by 100+ elements. And also there are one or two more array lists like that. So will it take much time in retrieving a document from Users collection? or not? And which will be a better approach?
Here are the images of my current database structure as Users and Friends.
As per the Firestore usage and limits, the maximum size of a document is 1 MiB.
It means that as long as your user documents don't exceed the size limit, you can store friends data in arrays without a problem.
If you are planning to exceed the threshold, you may want to look for other options like creating subcollections to scale better as size of the subcollection doesn't affect the parent document's size in any way.
I built a chat app in flutter with firebase using mapping for each chat Text(only one doc was used in chat between 2 users). I observed that after I filled 1MB of data in doc, my mobile downloaded the chat history at 10-12 kbps from firebase.
Maybe the speed was a coincidence but I am sure that as your data grows in a single firestore doc, the mobile app does not bursty download the whole document simultaneously, instead it downloads at a much slower speed.
Please correct me If I am wrong.
The article about Best practices for Cloud Firestore states that we should keep the rate of write operations for an individual collection under 1,000 operations/second.
But at the same time, the Firebase team says in Choose a data structure that root-level collections "offer the most flexibility and scalability".
What if I have a root-level collection (e.g. "messages") which expects to have more than 1,000 write operations/second?
If you think at that limitation of 1,000 operations/second it's pretty much but if you find your self in a situation in which you need more than that, then you should consider changing your database schema to allow writes on multiple collections. So you should multiply the number of collections. Having a single collection of messages, in which every user can add messages doesn't sound as a good way to go since you can reach that limitation very soon. In this case you should split that collection into multiple other collections. A possible schema might be the one I have explained in the following video:
https://www.youtube.com/watch?v=u3KwKQddPoo
See, at the end of that video, there is collection named messages which in term contains a roomId document. This document contains a subcollection named roomMessages which contains as documents all messages from a chat room. In this case, there are no chances you can reach that limitation.
But at the same time, the Firebase team says in Choose a data structure that root-level collections "offer the most flexibility and scalability".
But also rememeber, Firestore can as quickly look up a collection at level 1 as it can at level 100, so you don't need to worry about that.
The limit of 1,000 ops/sec per collection only apply to realtime update, so as long as you don't have a snapshot listener this should be okay.
I asked the question on the Cloud Firestore Google Groups
The limit is 10,000 writes per second if no other limits apply first:
https://firebase.google.com/docs/firestore/quotas#writes_and_transactions
Also just keep in mind the best practices for scaling cloud firestore
Understand firestore charge based on read / write operation.
But I notice that the firestore read from server per app launch, it will cause a big read count if many user open the app quite frequent.
Q1 Can I just limit user read from server for first time login. After that it just read for those update document per app launch?
For example there's a chat app group.
100 users
100 message
100 app launch / user / day
It will become 1,000,000 read count per day?
Which is ridiculous high.
Q2 Read is count per document, doesn't matter is root collection / sub collection, right?
For example, I read from a root collection that contain 10 subcollection and each of them having 10 documents, which will result 100 read count, am i right?
Thanks.
That’s correct, Cloud Firestore cares less about the amount of downloaded data and more about the number of performed operations.
As Cloud Firestore’s pricing depends on the number of reads, writes, and deletes that you perform, it means that if you had 100 users communicating within one chat room, each of the users would get an update once someone sends a message in that chat, therefore, increasing the number of read operations.
Since the number of read operations would be very much affected by the number of people in the same chatroom, Cloud Firestore suits best (price-wise) for a person-to-person chat app.
However, you could structure your app to have more chat rooms in order to decrease the volume of reads. Here you can see how to store different chat rooms, while the following link will guide you to the best practices on how to optimize your Cloud Firestore realtime updates.
Please keep in mind that Cloud Firestore itself does not have any rate limiting by default. However, Google Cloud Platform, has configurable billing alerts that apply to your entire project.
You can also limit the billing to $25/month by using the Flame plan, and if there is anything unclear in your bill, you can always contact Firebase support for help.
Regarding your second question, a read occurs any time a client gets data from a document. Remember, only the documents that are retrieved are counted - Cloud Firestore does searching through indexes, not the documents themselves.
By using subcollections, you can still retrieve data from a single document, which will count only as 1 read, or you can use a collection group query that will retrieve all the documents within the subcollection, counting into multiple reads depending on the amount of documents (in the example you put, it would be 10x10 = 100).
I'm building an app using flutter and firebase and was wondering what the best firestore database structure.
I want the ability for users to post messages and then search by both the content of the post and the posters username.
Does it make sense to create one collection for users with each document storing username and other info and a separate collection for the posts with each document containing the post and the username of the poster?
In the unlikely event where the number of posts exceeds a million or more, is there an additional cost of querying this kind of massive collection?
Would it make more sense to store each user's posts as a sub-collection under their user document? I believe this would require additional read operations to access each document's sub-collection. Would this be cheaper or more expensive if I end up getting a lot of traffic?
is there an additional cost of querying this kind of massive collection?
The cost and performance of reading from Firestore are purely based on the amount of data (number of documents and their size) you retrieve, and not in any way on the number of documents in the collection.
But what is limited in Firestore is the number of writes you can do to data that is "close to each other". That intentionally vague definition means that it's typically better for write scalability to spread the data over separate subcollections, if the data naturally lends itself to that (such as in your case).
To get a great introduction to Firestore, and to data modeling trade-offs, watch Getting to know Cloud Firestore.
Before creating a new app I wanna make sure I get the pricing model correct.
For example in a phonebook app, I have a collection called userList that has a list of users which are individual documents.
I have 50k users on my list, which means I have 50k documents in my collection.
If I were to get the userList collection it will read all 50k documents.
FireStore allows 50k document reads. Does that mean 50k document reads in total or 50k document read per document?
As in the example of my phonebook app if it is 50k document reads in total I will run out of the free limit in just one get call.
If you actually have to pull an entire collection of 50k documents, the question you likely should be asking is how to properly structure a Firestore Database.
More than likely you need to filter these documents based on some criteria within them by using the query WHERE clause. Having each client device hold 50k documents locally sounds like poor database planning and possibly a security risk.
Each returned document from your query counts as 1 read. If there are no matches to your query, 1 read is charged. If there are 50k matches, there are 50k reads charged.
For example, you can retrieve the logged in user's document and be charged 1 read with something like:
db.collection('userList').where('uid', '==', clientUID)
Note: As of 10/2018 Firestore charges 6 cents (USD) per 100k reads after the first 50k/ day.
The free quota is for your entire project. So you're allowed 50.000 document reads under the entire project.
Reading 50K user profile documents will indeed use that free quota in one go.
Reading large numbers of documents is in general something you should try to prevent when using NoSQL databases.
The client apps that access Firestore should only read data that they're going to immediately show to the user. And there's no way you'll fit 50K users on a screen.
So more likely you have a case where you're aggregating over the user collection. E.g. things like:
Count the number of users
Count the number of users named Frank
Calculate the average length of the user names
NoSQL databases are usually more limited in their query capabilities than traditional relational databases, because they focus on ensuring read-scalability. You'll frequently do extra work when something is written to the database, if in exchange you can get better performance when reading from the database.
For better performance you'll want to store these aggregation values in the database, and then update them whenever a user profile is written. So you'll have a "userCount", a document with "userCount for each unique username", and a "averageUsernameLength".
For an example of how to run such aggregation queries, see: https://firebase.google.com/docs/firestore/solutions/aggregation. For lower write volumes, you can also consider using Cloud Functions to update the counters.
Don't call all users in one go. You can limit your query to get a limited number of users. And when a user will scroll your query will get more users. And as no one is going to scroll fro 50k users so you can get rid of a bundle of cost. This is something like saving memory in case of recycle view.