Great question! This new storage allowed us to implement a really powerful label-based data model, much like labeling and selection of time-series in Prometheus

Great question! This new storage allowed us to implement a really powerful label-based data model, much like labeling and selection of time-series in Prometheus[1]. This is incredibly powerful when slicing and dicing data to find exactly what you're looking for. Many of our early users switched just because of this. Also, the eBPF based profiler we just released allows profiling targets with low overhead and best of all: no instrumentation needed. It automatically discovers targets to profile, which currently supports Kubernetes and systemd. So all you need to do to profile your entire infrastructure is to deploy the agent. Lastly we strongly believe in open standards, so the profiler produces pprof formatted profiles, and any pprof compatible profile can be written to Polar Signals / Parca. We also have exporting any query to a pprof formatted profile implemented but not exposed to the UI yet. The storage we specifically designed for all of this to work at scale and low latency and cost is also very interesting! Happy to dive more into details or talk about more things. [1] https://prometheus.io/ https://prometheus.io/