Parca vs Scalene
Parca
parca.devScalene
github.comSide by side
| Figure | Parca | Scalene |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | — |
| Plans published | 1 | 1 |
| Spec score · Profiling Software | 8.2 (#6) | 7.6 (#17) |
| Support | Polar Signals offers paid support for users of Parca’s open-source project. | The project links to a Scalene community Slack for community discussion. |
Plans
In their own words
Parca
Parca is a self-hosted profiling system that collects and stores CPU, memory, I/O, and other profiles for queries over time. Its eBPF-based Parca Agent captures user-space and kernel-space stack traces, while the system also accepts valid pprof-formatted profiles pushed through gRPC or pulled from targets over HTTP. Users can query by labels, compare dimensions such as processes or code versions, and view profiles in the web interface with Icicle Graphs. A Grafana plugin can display profiles stored in Parca. The agent supports automatic profiling for languages including C, C++, Go, Rust, .NET, Deno, Erlang, Java, Julia, Node.js, Wasmtime, PHP, Ruby, and Python. Installation options include binaries, containers, Kubernetes, and Snaps. Parca is open source under the Apache 2 License and is free. The agent requires Linux kernel 4.18 or newer and privileged access to load eBPF programs. Parca says it receives profiling statistics and function-name metadata, not binaries or source code.
Scalene
Scalene is a free, open-source profiler for Python programs that reports CPU, GPU and memory use and offers AI-powered optimization proposals. Its line- and function-level reports separate Python time from native-code and system time. Memory analysis shows per-line use, distinguishes Python from native allocations and flags lines with likely memory leaks. GPU profiling reports time on NVIDIA-based systems. Async profiling attributes wall-clock await time to the suspended coroutine line and reports mean and peak concurrent waiters. Its graphical interface can display stitched Python and native call stacks, memory flame charts and a timeline. Scalene is usable from the command line, a web-based GUI, a Visual Studio Code extension or Jupyter notebooks. The web interface processes profiles locally and works offline. For optimization suggestions, listed AI providers include Amazon Bedrock, Microsoft Azure, OpenAI and local models through Ollama. The project reports typical profiling overhead of no more than 10–20%, often less. Scalene is available for free under the Apache-2.0 license, with installations listed for macOS, Linux, Windows and Windows Subsystem for Linux 2.