Arc and Jira usually solve different primary problems. Jira is designed to plan and track work through issues, backlogs and configurable workflows. Arc is designed to manage connected engineering requirements, system relationships, change impact and verification evidence. Many teams should evaluate using them together rather than forcing one to replace the other.
Jira can represent requirements as issues and Atlassian publishes a requirements traceability matrix template based on issue links. That can work well for software and project delivery. The question is whether those work items provide enough engineering semantics, evidence and baseline control for the complete hardware or space programme.
Quick decision guide
- Choose Jira when: Your primary need is planning software work, managing backlogs and tracking delivery.
- Choose Arc when: Requirements must trace through system architecture to verification evidence.
- Validate the choice by: Represent one requirement hierarchy, interface, implementation task, test case and result in both workflows.
Arc vs Jira: comparison at a glance
| Criterion | Arc | Jira |
|---|---|---|
| Primary role | Requirements and verification workspace | Project and work management platform |
| Core object | Typed engineering items with explicit relationships | Configurable issues and work items |
| Traceability | Needs, requirements, systems, tests, results and evidence | Issue links, dependencies, custom fields and marketplace extensions |
| Change impact | Trace affected engineering relationships before approval | Track linked work and dependencies through configured workflows |
| Verification | Connect planned verification and objective evidence to requirements | Represent tests through issues, templates or integrated test tools |
| Planning | Programme context rather than sprint management | Strong backlogs, boards, timelines, dashboards and delivery workflows |
| AI | Agents configured for requirements, traceability and verification | Rovo AI and automation across Jira work management |
| Best fit | Systems, hardware and V&V teams managing engineering intent | Software and cross-functional teams planning and delivering work |
What Jira is built for
Jira is a flexible work-management platform with configurable fields, workflows, boards, timelines, dashboards, automation, APIs and a large integration marketplace. Teams can create requirement issues and link them to tasks, stories or tests.
That flexibility is valuable because developers can stay in a familiar delivery environment. It can also encourage teams to build a bespoke requirements system from issue types, plugins and conventions. The suitability of that system depends on the complexity of traceability, baselines, verification evidence and formal review.
Why teams evaluate an alternative
Teams usually evaluate an alternative to Jira for requirements management when the configured issue model can no longer answer systems-engineering questions reliably. Jira may still manage delivery extremely well; the pressure appears when hierarchy, formal trace semantics, baselines, verification evidence and cross-disciplinary review are implemented through growing numbers of fields, links, conventions and marketplace applications.
This is often an ownership decision rather than a replacement decision. Atlassian's requirements traceability matrix template uses Jira work items and issue links to connect requirements with tasks and tests. A space programme must decide whether those records represent engineering intent, delivery work, or both.
Capability-by-capability comparison
Requirements authoring and data model
Atlassian describes Jira work items as configurable records for work such as features, user requirements and bugs. Teams can create requirement issue types, fields and templates. Arc begins with typed engineering items and explicit programme relationships. Compare rationale, source, hierarchy, interfaces and verification attributes rather than text fields alone.
Traceability, baselines and change control
Jira issue links can express dependencies and requirement-to-task relationships, but the team defines link semantics, coverage rules and reports. Apps may add hierarchy or traceability matrices. Arc is intended to model upstream and downstream engineering relationships and review a connected change before merge. The pilot should distinguish a linked work dependency from a formal satisfies, verifies or derives relationship.
Reviews, verification and evidence
Jira workflows, comments and approvals can support review, while test management commonly depends on configured issue types, automation or marketplace applications. Arc keeps test cases, results and objective evidence in the requirements context. Compare how each approach handles a failed test, changed requirement, approval record and review-ready verification matrix.
Deployment, administration and integrations
Jira's marketplace and APIs make it highly extensible and familiar to software teams. The operating cost appears in schema governance, app selection, automation, permissions and custom reports. Arc introduces another platform and an integration boundary, but can give systems and verification teams a purpose-built model while Jira remains authoritative for implementation work.
Aerospace and space programme fit
Jira alone can be appropriate for a software-heavy subsystem with lightweight requirements and strong issue discipline. For a complete spacecraft programme, test whether mechanical, electrical, systems, safety and V&V contributors can represent and review the engineering relationships they need without translating every concept into a generic work item.
At PDR or CDR, require a current requirement baseline, traceability coverage, unresolved interface changes and verification readiness. For supplier collaboration, establish whether suppliers receive Jira access, a controlled export or requirements from Arc. Delivery completion in Jira should not automatically imply requirement acceptance or verification closure.
Total operating cost and implementation effort
For Jira, include edition costs, marketplace applications, administration, workflow and field governance, reporting, integration maintenance and the specialist effort needed to keep the requirements model consistent. Existing developer adoption and delivery integrations are significant benefits that should remain in the calculation.
For Arc, include commercial pricing, implementation, user rollout and the Arc-to-Jira integration or exchange process. The business case should measure reduced requirements administration, clearer impact analysis and faster review preparation while recognising the cost of operating two systems with a defined ownership boundary.
Migration and adoption path
Do not begin by moving every Jira issue. Identify which records are authoritative engineering requirements and which are epics, stories, tasks, defects or tests. Move the requirement text, rationale, hierarchy and formal relationships to Arc while retaining delivery history in Jira unless there is a clear reason to migrate it.
Pilot one subsystem with stable identifiers between Arc requirements and Jira implementation work. Define update direction, duplicate-field policy and what happens when either side changes. Run one failed-test and requirement-change scenario before automating synchronisation, then monitor unmatched and stale links as an operational control.
When Arc may not be the right choice
Arc may not be the right choice when requirements are genuinely lightweight, closely match software backlog items and the Jira workflow already provides sufficient review and traceability. Adding a dedicated requirements platform without a clear ownership boundary can increase tool switching and create duplicate records.
Where Arc takes a different approach
- Engineering objects first. Arc begins with requirements, systems, interfaces, tests and evidence rather than general-purpose issues.
- Programme change impact. The model is intended to show how a proposed requirement change affects connected engineering work.
- Verification context. Test cases, results and evidence remain connected to the requirements they verify.
- Controlled branches. Engineers can review a complete connected change before merging it into the baseline.
Which option should your team choose?
Choose Jira when
- Your primary need is planning software work, managing backlogs and tracking delivery.
- Requirements are lightweight and can be represented reliably with issues and links.
- Your organisation is deeply invested in Atlassian workflows and marketplace applications.
- Developers should remain in the same tool for requirements and execution.
Choose Arc when
- Requirements must trace through system architecture to verification evidence.
- Hardware, systems and V&V contributors need more engineering context than issue links provide.
- Change impact and baseline review are central programme controls.
- You want AI assistance grounded in a connected engineering model.
What to test before making a decision
Do not decide from a feature checklist alone. Use one active subsystem and run the same engineering change through both candidate workflows.
- Represent one requirement hierarchy, interface, implementation task, test case and result in both workflows.
- Change the parent requirement and identify every affected object without relying on team memory.
- Prepare a review-ready traceability view and evidence package.
- Measure how much Jira configuration, plugin management and custom reporting the target workflow requires.
Can Arc and Jira work together?
Yes. A common boundary is for Arc to own engineering requirements, relationships and verification context while Jira owns implementation tasks, bugs and delivery planning. Teams should validate identifier mapping, update direction and review ownership before relying on an integration.
The bottom line
Jira is excellent at managing work; Arc is intended to manage the engineering intent and evidence behind that work. Use Jira alone when requirements are lightweight. Evaluate Arc alongside Jira when system traceability and verification become a programme discipline.
Related Arc comparisons
- Arc vs open-source requirements management tools
- Arc vs requirements spreadsheets
- Arc vs PTC Codebeamer
To see the wider market before shortlisting a platform, read the best requirements management tools for aerospace and space teams. For an implementation-level traceability example, use the requirements traceability matrix guide and template.
Frequently asked questions
Can Jira be used for requirements management?
Yes. Teams can model requirements with issue types, custom fields, links, workflows and extensions. The approach should be tested against required hierarchy, baselines, review, traceability and verification evidence.
Does Arc replace Jira?
Not necessarily. Arc focuses on requirements and verification, while Jira focuses on planning and tracking work. Many organisations may use both with a clear ownership boundary.
What should remain in Jira?
Implementation tasks, defects, sprint planning and delivery status are natural Jira records. The authoritative engineering requirement, its rationale, relationships and verification evidence can remain in Arc.
What is the difference between a Jira link and a formal trace link?
A Jira link connects work items using team-defined semantics. A formal trace link has an agreed engineering meaning, coverage expectation and change-impact role such as derives, satisfies or verifies.
Does requirements management in Jira require plugins?
Lightweight requirements can use native work items, fields and links. More specialised hierarchy, test management, baselines or traceability reporting may require additional configuration or marketplace applications.
How should Arc and Jira divide ownership?
Arc can own engineering requirements, relationships and verification context, while Jira owns implementation tasks, defects and delivery planning. Stable identifiers should connect the two.
Evaluate Arc on a real programme workflow
Bring one representative requirement set, one proposed change and its verification evidence. Arc can then be assessed against the workflow and controls your team actually needs. Book a working session with Arc.