Weave vs. LinearB
Engineering teams today have access to numerous tools designed to provide insights into development workflows and team performance. Two notable options in this space are LinearB and Weave. Both platforms aim to help engineering leaders make data-driven decisions, but they take different approaches to achieving this goal.
Go Beyond Automation, Lead with Intelligence
LinearB has established itself as a solid choice for teams looking to track workflow metrics and gain visibility into their development processes. The platform provides comprehensive dashboards and helps teams understand their delivery patterns through automated data collection from tools like Jira and GitHub.
Weave takes a different approach by focusing on AI. Rather than stopping at workflow automation, Weave attempts to provide deeper insights into the quality and impact of engineering work. They do this by scanning every PR and answering the questions “how long would it take an expert engineer to complete this?” The result is 94% accuracy in measuring objective output per engineer.
See How We Compare
Feature | Weave | LinearB |
|---|---|---|
Team Health | ||
DORA and Productivity Metrics | ✅ | ✅ |
Lifecycle Metrics | ✅ | ✅ |
Collaboration Metrics | ✅ | ✅ |
Team Comparison | ✅ | ✅ |
Business Alignment | ||
Timeline-Based Investment Allocation | ✅ | ✅ |
Executive Reporting & Planning | ✅ | ✅ |
Industry Benchmarks | ✅ | ✅ |
Benchmarking Cohorts | ✅ | ✅ |
Financial Reporting | ||
Budgeting, Forecasting & Analysis | ❌ | ✅ |
Product Portfolio Cost Analysis | ❌ | ✅ |
Process Management | ||
Status Tracking and Reporting | ✅ | ✅ |
Allocation by Deliverable | ✅ | ✅ |
Delivery Predictions and Scenario Planning | ✅ | ✅ |
Code Review | ||
Code Review Quality | ✅ | ❌ |
Code Review Depth | ✅ | ❌ |
Code Review Turnaround | ✅ | ✅ |
Core Technology & Metrics | ||
ML-Driven Output Assessment | ✅ Yes, proprietary ML model | |
Correlation to Real Engineering Effort | ✅ 0.94 accuracy | ❌ |
Security | ||
SOC-1 Type II Financial Compliance | ✅ Weave is in the observation period | ✅ |
Administration | ||
Fully Self-Service Configuration | ✅ | ✅ |
SSO | ✅ | ✅ |
Role and Group Based Access Controls | ✅ | ✅ |
Integrations & Accessibility | ||
Key Integrations (e.g., Jira, GitHub) | ✅ | ✅ |
AI | ||
AI Effectiveness | ✅ | ❌ |
AI Usage | ✅ | ✅ |
Individual AI Reports | ✅ | ❌ |
Pricing & Support | ||
Free Version | ✅ | ❌ |
Comprehensive Support (Business hours, 24/7 live rep, online) | ✅ | ❌ |
Solve Your Toughest Engineering Challenges
When LinearB Might Be Preferred
Teams that need straightforward workflow tracking and are satisfied with standard DORA metrics may find LinearB sufficient for their needs. The platform works well for organizations that want to establish baseline performance measurements without requiring deep qualitative analysis.
When Weave's Approach Offers Advantages
Organizations looking to go beyond basic workflow metrics may benefit from Weave's AI-driven approach. The platform's ability to analyze code review quality and provide individual developer insights could be valuable for teams focused on continuous improvement and code quality enhancement.
Teams looking to quantify the impact of AI and identify the teams best practices will likely lean towards Weave.
Ready to See the Full Picture?
The decision between LinearB and Weave ultimately depends on your team's specific needs and maturity level. Teams seeking comprehensive workflow tracking with proven reliability may find LinearB meets their requirements effectively. Organizations looking for deeper insights into code quality and more sophisticated business alignment features may find Weave's AI-driven approach more aligned with their goals.
Weave offers a free version, making it possible to evaluate their capabilities before committing to a paid plan. This allows teams to assess which approach better fits their workflow and provides the most valuable insights for their specific context.
