As @akulkarni said, Promscale supports Prometheus metrics and OpenTelemetry traces natively and there are different ways to correlate both signals. I am actually delivering a talk that goes over the different ways you can correlate Prometheus and OpenTelemetry data tomorrow at Prometheus Day :)
One is via adding exemplars to your Prometheus metrics that link to specific traces that are representative of the value of those metrics. In Promscale you can store all that information and then display it in Grafana as explained in 1. That's the way that is most often discussed but typically involves deploying one backend for metrics and one backend for traces instead of just one as is the case with Promscale.
With Promscale you can also correlate metrics and traces using SQL joins. That opens a whole set of new possibilities. For example, imagine if you could retrieve the slowest requests happening on services running on nodes where CPU usage is high to understand how they are impacting their performance. Or imagine you are seeing a specific OOM error often in your traces and you could run a SQL query to look at the evolution of memory usage in the last 24 hours of nodes where those OOM errors are more frequent to see if you spot anything strange happening. You could even go a step forward andretrieve in the same query what processes are consuming the most memory in those nodes to pinpoint the processes that could be causing the issue.
[1] https://grafana.com/docs/grafana/latest/basics/exemplars/