CDviz vs LinearB

Both platforms surface engineering metrics for software delivery teams. They solve different problems with fundamentally different approaches.

Last updated March 2026. Corrections welcome.

At a glance

	CDviz	LinearB
License	Apache 2.0	Proprietary
Self-hosted	✅	❌
SaaS option	⏳ waitlist	✅
Free tier	✅ self-host	✅ (up to 8 contributors)
Commercial support	✅	✅ (included)
Data ownership	✅ full	❌ vendor-hosted
CDEvents standard	✅ native	❌
Data model	Event-driven (push)	Pull-based (polling)
DORA metrics	✅	✅
PR / cycle time analytics	⏳ planned	✅ (core strength)
Beyond monitoring: trigger workflows	✅	✅ (PR automations / AI actions)
Built-in integrations	GitHub, GitLab, ArgoCD, Kubernetes…	GitHub, GitLab, Jira, Linear…
Customizable storage backends	✅ (PostgreSQL, ClickHouse…)	❌
Visualization	Grafana, BI, AI agents, MCP, IDP tools	built-in dashboards
Pricing model	Infra + optional support	~$420–$549 per contributor/year

Key differences

• Event-driven vs poll-based: CDviz receives events in real-time as they happen (push model). LinearB periodically polls your git provider and issue tracker APIs — simpler to onboard but introduces latency and heavier API load.
• Scope of observability: LinearB excels at git and PR-centric metrics — cycle time, PR review depth, merge frequency. CDviz covers the full delivery pipeline including deployments, incidents, artifact promotion, and Kubernetes events via CDEvents.
• Open standard vs proprietary model: CDviz stores events using the open CDEvents specification, keeping your data vendor-neutral and portable. LinearB's data model is proprietary and tied to its platform.
• Data ownership: With CDviz, your SDLC data stays in your infrastructure (or with CDviz via the SaaS waitlist). LinearB stores all data on its own servers.
• Automation scope: LinearB's workflow automation is focused on PR lifecycle — routing reviews, auto-merging low-risk changes, AI code context. CDviz's event-driven approach lets you trigger any downstream system (Slack, incident tools, deployment pipelines, etc.) based on any SDLC event.
• Visualization flexibility: LinearB provides opinionated built-in dashboards aimed at engineering managers. CDviz connects to any visualization layer — Grafana, BI platforms, AI agents, MCP-connected tools, Internal Developer Platforms.
• Cost at scale: LinearB pricing grows linearly with contributor count ($420–$549/contributor/year). CDviz self-hosted costs scale with infrastructure, not headcount.

When to choose CDviz

• You want full ownership of your SDLC data with no vendor lock-in.
• You are adopting or building on the CDEvents open standard.
• You need visibility beyond git/PRs — deployments, incidents, Kubernetes, artifact timelines.
• You need real-time events rather than periodic snapshots.
• You want events to trigger downstream workflows across your toolchain.
• Your team already runs Grafana and wants SDLC visibility alongside infra/app dashboards.
• You need flexible storage (PostgreSQL, ClickHouse) or reporting (BI, AI, MCP, IDP).
• Cost at scale is a concern — CDviz does not charge per contributor.

When to choose LinearB

• Your primary need is git and PR-centric metrics (cycle time, PR size, review depth, merge frequency) with minimal configuration.
• Engineering managers want pre-built dashboards and benchmarks (LinearB publishes industry benchmarks from 4,800+ organizations).
• You need AI-powered PR review routing and merge automation out of the box.
• Your team uses Jira or Linear for project tracking and wants tight integration.
• A managed SaaS with near-zero operational overhead is a priority.

Summary

LinearB is the fastest path to PR-centric engineering metrics and AI-powered code review workflows for teams already using GitHub/GitLab and Jira. CDviz is the right choice when you need full-pipeline observability beyond git, data ownership, an open event standard, real-time event streaming, or cost efficiency at scale — with commercial support available to reduce operational risk.