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DeepFlow vs Parca

DeepFlow

deepflow.io

Parca

parca.dev

Side by side

FigureDeepFlowParca
Price fromFreeFree
Free planYesYes
Free trialYes—
Open source——
WebYesYes
WindowsYes—
LinuxYesYes
AndroidYes—
APIYesYes
Self-hostedYesYes
Plans published31
Spec score · eBPF Observability Tools8.1 (#8)8.1 (#9)
DeploymentThe documentation provides Kubernetes and Docker Compose deployment methods for an all-in-one installation.The project documents installation using binaries, containers, Kubernetes, and Snaps.

Plans

DeepFlow

  • Community EditionFree
  • Cloud EditionPriced on request
  • Enterprise EditionPriced on request

DeepFlow pricing →

Parca

  • Parca Open SourceFree

Parca pricing →

In their own words

DeepFlow

DeepFlow is an observability product for cloud infrastructure and cloud-native applications. It uses eBPF to collect application performance metrics, distributed traces, and continuous profiling data without intrusion. Its core capabilities include a universal service map, distributed tracing, and profiling. Built-in parsing covers HTTP, HTTPS, Dubbo, gRPC, MySQL, PostgreSQL, Redis, MongoDB, Kafka, MQTT, and DNS. DeepFlow can serve as storage for Prometheus, OpenTelemetry, SkyWalking, and Pyroscope, and offers SQL, PromQL, and OTLP interfaces. AutoTagging links observability data with cloud and Kubernetes resources, tags, and CMDB business tags. The Community Edition is open source under Apache 2.0 and is listed at free. It supports Linux servers and selected Kubernetes, cloud, and container environments; deployment guidance covers Kubernetes and Docker Compose. Enterprise Edition adds encrypted agent-to-server transmission, multi-tenancy, and data permission isolation. The listed platforms include Android, API, Linux, self-hosted, web, and Windows.

Visit deepflow.io

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.

Visit parca.dev