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CDviz vs Apache DevLake

Both are open-source platforms for engineering metrics and SDLC visibility. They take different approaches.

Last updated February 2026. Corrections welcome.

At a glance

CDvizApache DevLake
LicenseApache 2.0Apache 2.0
Self-hosted
SaaS option⏳ waitlist
Commercial support
CDEvents standard✅ native
Data modelEvent-driven (push)Pull-based (polling)
Beyond monitoring: trigger workflows
DORA metrics
Built-in integrationsGitHub, GitLab, ArgoCD, Kubernetes…50+ (Jira, Jenkins, PagerDuty, SonarQube…)
Customizable storage backends✅ (PostgreSQL, ClickHouse…)
VisualizationGrafana, any analytics / AI / IDP toolbuilt-in Grafana dashboards
MaturityEarly stageIncubating @ Apache

Key differences

  • Standard vs custom model: CDviz uses the open CDEvents specification as its event schema. DevLake uses a proprietary domain model. CDviz data is inherently portable; DevLake data is optimized for its own dashboards.
  • Push vs pull: CDviz collects events in real-time as they happen. DevLake polls APIs on a schedule — simpler to start but introduces latency and heavier API load.
  • Observe and act: CDviz events are not read-only. The same event stream used for observability can trigger downstream workflows — making it an event-driven SDLC backbone, not just a dashboard. DevLake is monitoring-only.
  • Customization depth: CDviz lets you enrich events at ingestion (add context, normalize fields), route to different storage backends (PostgreSQL, ClickHouse…), and visualize in any tool — Grafana, BI platforms, AI agents, MCP-connected tools, Internal Developer Platforms.
  • Ecosystem breadth: DevLake has significantly more ready-made integrations today. CDviz relies on webhooks and community-contributed transformers.
  • Commercial support: CDviz offers commercial support, making total cost of ownership lower than self-managing an unsupported open-source stack.

When to choose CDviz

  • Your team wants to adopt or contribute to the CDEvents open standard.
  • You need real-time event streaming (not periodic snapshots).
  • You want events to trigger workflows — not just be observed.
  • You already run Grafana and want to add SDLC visibility to existing dashboards.
  • You need flexible storage (ClickHouse, PostgreSQL) or reporting (BI, AI, MCP, IDP).
  • You want commercial support without building and maintaining everything yourself.
  • You prefer a managed SaaS option (join the waitlist).

When to choose Apache DevLake

  • You need broad out-of-the-box integrations (Jira, Jenkins, PagerDuty, SonarQube…) without writing custom collectors.
  • Your team prefers a batteries-included setup with less configuration.
  • Monitoring and dashboards are sufficient — no need to trigger workflows.

Summary

DevLake is the safer "broad coverage" choice for pure metrics and dashboards. CDviz is the right bet if open standards, real-time events, event-driven automation, and composable tooling matter to your team — or if you want commercial support to reduce operational risk.