reactfire VS googleapis

ReactFire

Are you using Firebase? If not, you probably should. You can call functions (with Auth) from your react app. There's a framework you can use to help: https://github.com/FirebaseExtended/reactfire

I was an early developer at Firebase. I think we made Firebase so easy to use and never spoke on about the technicals that the whole software ecosystem now underestimates the complexity involved. I see various Firebase competitors asserting various "mistakes it makes" without really understanding what it delivers, which is understandable because we never marketed it like that because we spoke only about how it can help you build easier.

The idea that n queries instead of a join is slow is not as true as you would think. Firestore supports streaming and pipelines at its core, and can reuse cache across operations. At the end of the day, the data goes over a narrow network channel. If you can saturate the channel, and don't leave any gaps, what's the performance difference if the data comes from a single query or many that are back-to-back. The data is transferred to the client either way. Both Firebase databases are pipelined, so this "many round trip" argument is not a decent argument if the client can issue the queries without waiting for responses (such as the code in this article).

The other is consistency levels and correctness. I constantly see devs call Firebase an eventually consistent database which is wrong, its causally consistent [1], and this makes a huge difference when trying to do OLTP. The offline capabilities are built on the consistency primitives, and it's the only way it can work. So while this convex article is banging on about "End-to-End Correctness Philosophy", they miss the most important quality of correctness, and if they are not careful, will miss the required engineering, and then be unable to deliver an offline cache over real-time streams. I see this playing out with Supabase, I warned them personally before they got into YCombinator that what they were building was not causally consistent. Since then, they have had to rearchitect their real-time features after shipping them. (I have not reviewed their latest design yet so I have no idea whether they have it right yet).

Many things sucked about Firebase. The bespoke security rules and the lack of views. So Convex is on the money shipping functions on the backend. I think Supabase is shipping competitors' mistakes with row-level security language. Personally, I think Firebase's mistakes can be fixed with the addition of an open-source Firebase server [1], as the clients are already open source and the mistakes are all to do with just the server. The real tech was always in the clients anyway (offline cache, connection management, operation queues).

It will be interesting to see if building expressly for React is a good idea. Firebase shipped many adapters, like https://github.com/FirebaseExtended/reactfire, using the "thin-waist" principle of not over-fitting. But Javascript technology moved from callbacks to async while Firebase was in the field, so the current API is not now idiomatic. But convex is setting itself for even more ecosystem fragility, what if React changes API or falls out of favor? This is a big risk! I hope they can roll with whatever happens!

[1] https://observablehq.com/@tomlarkworthy/redis-backend-1

Since you mentioned you're also using React, we have a React specific library (ReactFire) that also helps out quite a bit.

Use ReactFire! It's our official library for React and Firebase. It has a bunch of useful hooks that probably handle most of the actions you are looking to do.

This is a quick walkthrough of a code example using ReactFire v4 in an application. The application supports login, logout, create an account, and protected routes. We also walk through two approaches for protecting routes since the AuthCheck component that existed in v3 no longer exists in v4 of ReactFire.

FWIW check out ReactFire, it gives you hooks and context for Firebase. Will likely feel more natural than using the vanilla platform-agnostic SDK.

reactfire

Rich Error Model: This model enables servers to return and clients to consume additional error details expressed as one or more protobuf messages. It further specifies a standard set of error message types to cover the most common error (QuotaFailure, PreconditionFailure, BadRequest, etc). When an error occurs, the server returns the appropriate status code along with an optional error message.

They list search in their public api

https://github.com/googleapis/googleapis/blob/288aa7fb71c9b6...

We structure the repo according to proto packages. It's quite similar to how the googleapis repository is structured.

It's unfortunate that the spec doesn't contain custom fields to a sub-object like other RPC specs, like proto Status [1]. They should have had the message go into a field named "message" and not "detail". And have a field like "details" where the opaque type is serialized, which should be named by the "type" field. The problem is that systems with existing error types may have field name conflicts with type, title, status, detail, or instance, so we'd just dump the actual error into a custom "extension member" which by definition, isn't standard.

[1] https://github.com/googleapis/googleapis/blob/1c8a25ab153eef...

Protobuf (https://github.com/googleapis/googleapis)

All the required changes can be viewed in our last demo, the grpc-rest-app implementation. First, we need to update our proto service interface to help the proxy service make our gRPC service methods available at the right URLs and for the correct HTTP operations. To do this, the Google API HTTP library provides annotations we can add to our proto to describe the correct mappings. The buf tool allows us to include the googleapis dependency as a plugin in our buf.yaml file).

I think this only makes sense if the 3rd party is also throwing custom exceptions.

If you want to reduce coupling you should avoid throwing custom exceptions at all. Semantic information can go in the error message and log. The error type should be used to indicate to your program whether an error is recoverable, retriable or some other action needs to be taken. For example google on has 16 canonical error codes for all APIs.

https://github.com/googleapis/googleapis/blob/master/google/...

OpenAPI and possibly developing reusable, versioned client libraries could help, but it's a major undertaking that gRPC makes redundant. I'd be tempted to use grpc-gateway even if I had to implement a REST API. Try looking into buf and monorepo structures for proto management, e.g. something like GoogleCloudPlatform/microservices-demo. For more thorough proto and grpc-gateway definition examples, see googleapis/googleapis.

Firestone does provide global consistency, so the following quote is incorrect:

> In Cloud Firestore, the data on the client are loaded from the database at different points in time. Even if you listen for realtime updates, results from separate queries will not remain in sync. This creates consistency anomalies and bugs in your app.

Here is a link to the protocol documentation that the clients use to support it: https://github.com/googleapis/googleapis/blob/d0b394f188e8c3...

I'd link to the client implementation but it's quite involved.

Well there is Timestamp defined as a well known type which is available to all implementations despite not being a primitive type [1]. Plus one is obviously able to define any other custom types if necessary- eg as seen in [2].

[1] https://developers.google.com/protocol-buffers/docs/referenc...

[2] https://github.com/googleapis/googleapis/blob/master/google/...