But even without network issues that have plagued it I would hesitate to build anything for production on it because it can't even do transactions and the product manager for D1 openly stated they wont implement them [0]. Your only way to ensure data consistency is to use a Durable Object which comes with its own costs and tradeoffs.
https://github.com/cloudflare/workers-sdk/issues/2733#issuec...
The basic idea of D1 is great. I just don't trust the implementation.
For a hobby project it's a neat product for sure.
How did you work around this problem? As in, how do you monitor for hung queries and cancel them?
> D1 reliability has been bad in our experience.
What about reads? We use D1 in prod & our traffic pattern may not be similar to yours (our workload is async queue-driven & so retries last in order of weeks), nor have we really observed D1 erroring out for extended periods or frequently.
You just wrap your DB queries in your own timeout logic. You can then continue your business logic but you can't truly cancel the query because well, the communication layer for it is stuck and you can't kill it via a new connection. Your only choice is to abandon that query. Sometimes we could retry and it would immediately succeed suggesting that the original query probably had something like packetloss that wasn't handled properly by CF. Easy when it's a read but when you have writes then it gets complicated fast and you have to ensure your writes are idempotent. And since they don't support transactions it's even more complex.
Aphyr would have a field day with D1 I'd imagine.
> What about reads? We use D1 in prod & our traffic pattern may not be similar to yours (our workload is async queue-driven & so retries last in order of weeks), nor have we really observed D1 erroring out for extended periods or frequently.
We have reads and writes which most of the time are latency sensitive (direct user feedback). A user interaction can usually involve 3-5 queries and they might need to run in sequence. When queries take 500ms+ the system starts to feel sluggish. When they take 2-3s it's very frustrating. The high latencies happened for both reads and writes, you can do a simple "SELECT 123" and it would hang. You could even reproduce that from the Cloudflare dashboard when it's in this degradated state.
From the comments of others who had similar issues I think it heavily depends on the CF locations or D1 hosts. Most people probably are lucky and don't get one of the faulty D1 servers. But there are a few dozen people who were not so lucky, you can find them complaining on Github, on the CF forum etc. but simply not heard. And you can find these complaints going back years.
This long timeframe without fixes to their network stack (networking is CF's bread and butter!), the refusal to implement transactions, the silence in their forum to cries for help, the absurdly low 10GB limit for databases... it just all adds up. We made the decision to not implement any new product on D1 and just continue using proper databases. It's a shame because workers + a close-by read replica could be absolutely great for latency. Paradoxically it was the opposite outcome.
Also note that as of recently, the concurrent limit applies only up to the point that response headers are received, not during body streaming.
No downtime snapshots would be the best but I'd be quite happy with a blocking backup on a set schedule that can be set from the GUI / from the cli / from a config file. Its a huge PITA having to play 'trust me bro' to clients and their admins with custom workers and backups.
I currently stream it D1 dump -> worker(encrypt w/ key wrapping) -> R2 on a schedule, then have a container spin up once a day and create changesets from the dumps. An external tool pulls the dumps and changesets.
Cloudflare seems to be building for lock-in and I don't love it. I especially don't understand how you build an OpenRouter and only have bindings for your custom runtime at launch.
But in practice, it's basically impossible to use that way in conjunctions with workers, since you have to bind every database you want to use to the worker and binding a new database requires redeploying the worker.