Project Management migration

Migrate from Backlog to Jira

Field-level mapping, validation, and rollback between Backlog and Jira. We move data and schema; workflows are rebuilt natively in Jira.

Backlog logo

Backlog

Source

Jira

Destination

Jira logo

Compatibility

92%

11 of 12

objects map 1:1 between Backlog and Jira.

Complexity

BStandard

Timeline

2-4 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Backlog to Jira is primarily an issue-tracking and hierarchy migration with three structural shifts to resolve. First, Backlog's parent-child Subtask model maps to Jira's dedicated Subtask issue type within an issue type scheme — we create the scheme and configure the link type during schema design so subtasks land correctly. Second, Backlog's Custom Fields (available only on Premium and Enterprise) must map to Jira's custom field types because the field type inventory differs; we detect the source plan tier during discovery and skip the custom field step entirely on Free, Starter, or Standard accounts where no custom fields exist. Third, Backlog Wikis use a custom markup format that we convert to plain text or Jira-compatible wiki markup, flagging any macros without a direct equivalent for manual review. We do not migrate Backlog's Gantt chart visualizations, burndown charts, notification settings, or Workflow configurations — these are configuration elements that require rebuild in Jira. The migration uses Backlog's REST API for export and Jira's REST API for import, with empirical rate-limit probing on the Backlog side given that Backlog does not publish specific request-per-minute thresholds.

Field-level fidelity

Every standard and custom field arrives verified.

Schema-aware mapping

AI proposes the map; you confirm before any record moves.

Relationships preserved

Parent–child, lookups, and ownership stay linked.

Full activity history

Calls, emails, meetings — with original timestamps.

Attachments & notes

Documents, uploads, and inline notes move with the record.

Why teams make this switch

Two sides of the same decision

Leaving

Backlog logo

Backlog

What's pushing teams away

  • The reporting and analytics features are widely described as weak — G2 and Capterra reviewers flag the lack of advanced dashboards and custom reports as a recurring frustration.
  • Teams with complex workflows find the customization options limited, especially on lower tiers where custom fields are not available.
  • Exporting project lists to CSV or Excel drops full task descriptions — reviewers note the output omits issue text, forcing users to open each item manually.
  • The visual design and UI customization feel dated compared to newer project management tools, leading some teams to migrate for a more modern experience.
  • Some users report that Backlog's notification system is noisy and difficult to configure cleanly for large teams.

Choosing

Jira logo

Jira

What's pulling them in

  • Industry-standard tool with deep Git integration and sprint reporting that engineering teams already know, reducing onboarding friction for new hires.
  • Highly customizable workflows and status schemes let business teams model complex approval chains without writing code.
  • Strong ecosystem of Atlassian Marketplace apps means specialized capabilities like time tracking or portfolio management are one install away.
  • Free tier with up to 10 users and unlimited issues gives small teams a no-cost entry point to validate the platform before committing budget.
  • Visibility features — boards, backlog grooming, sprint reports, and dashboards — give leadership a shared view of what is planned, in progress, blocked, and done.

Object mapping

How Backlog objects map to Jira

Each row shows how a Backlog object lands in Jira, including any object-level transformations, lookup resolution, or schema-design dependencies.

Typical mapping — final map is confirmed during the sample migration step.

Backlog

Project

maps to

Jira

Project

1:1
Fully supported

Backlog Projects map directly to Jira Projects as the top-level container. We preserve the project key, name, description, project-level categories, and notification settings. Each Backlog project becomes one Jira project with its own issue type scheme, workflow, and field configuration. Project-level permission schemes are noted for manual configuration in Jira because Jira handles project permissions through permission schemes and project roles rather than Backlog's role model.

Backlog

Issue

maps to

Jira

Issue (Story, Task, Bug)

1:1
Fully supported

Backlog Issues map to Jira Issues with the type determined by Backlog's issue type name. Standard Backlog issue types (Task, Bug, Story, Enhancement) map to their Jira equivalents via the issue type scheme we configure before migration. Issue summary, description, status, priority, assignee, reporter, due date, start date, estimated hours, and spent hours all map to typed Jira fields. We preserve issue key references and Backlog's issue ID in a custom field backlog_issue_id__c for traceability.

Backlog

Subtask

maps to

Jira

Subtask

1:1
Fully supported

Backlog Subtasks map to Jira Subtask issue types linked to their parent Issue via the Jira Subtask issue link. We configure the Jira issue type scheme to include Subtask before migration. The subtask status, assignee, priority, and description migrate directly; estimated and logged hours are preserved as subtask fields. Parent issue ID is resolved at migration time using the backlog_issue_id__c custom field to maintain the parent-child relationship across the API import.

Backlog

Custom Field (Premium+)

maps to

Jira

Custom Field

lossy
Fully supported

Backlog Custom Fields exist only on Premium and Enterprise plans. On Free, Starter, and Standard accounts, this step is skipped entirely — we detect the plan tier during discovery and proceed without custom field mapping if none are configured. On Premium accounts, we map Backlog field types (text, numeric, date, list, multi-list, checkboxes, radio, dropdown) to the closest Jira custom field type (Free Text, Number, Date Picker, Select, Multi-Select, Checkboxes, Radio Buttons, Cascading Select). Fields that cannot map directly become Jira Free Text fields, and any unmappable field type is flagged in the reconciliation report.

Backlog

Tag

maps to

Jira

Label

1:1
Fully supported

Backlog Tags are free-form flat labels applied to issues. They map directly to Jira Labels, which are single-value string fields on Jira issues. Backlog's tag set is reconstructed as a Jira label scheme. Jira Labels are not hierarchical, matching Backlog's tag model, so no structural transformation is required.

Backlog

Milestone (Version)

maps to

Jira

Version

1:1
Fully supported

Backlog Milestones (called Versions in the Backlog UI) map to Jira Versions attached to the corresponding project. We preserve the milestone name, planned release date, and description. Issue-milestone associations migrate as Jira fixVersion references on each affected Issue, so the backlog of issues in a given release is visible directly in the Jira release report.

Backlog

Category

maps to

Jira

Component

1:1
Fully supported

Backlog Categories group issues at the project level and can represent product areas, services, or team assignments. We map them to Jira Components within each project. Component lead, description, and assignee are preserved where configured in Backlog. Issues are linked to their Component via the Component field on the Jira issue.

Backlog

User

maps to

Jira

User

1:1
Fully supported

Backlog Users are mapped to Jira Users by email address match. User display name, email, and role are extracted from Backlog. Any Backlog user without a matching Jira account is flagged in the reconciliation report for the customer's admin to provision before the record import phase. Jira requires an active or inactive user to be present before Owner or Assignee fields can be populated.

Backlog

Team (Group)

maps to

Jira

Group

1:1
Fully supported

Backlog Teams are group-level assignments that can be assigned to issues rather than individual users. We map Teams to Jira Groups. Team membership and team-issue assignments are preserved as Jira group memberships on the relevant issues. Jira Groups are used for notifications and project role membership but do not replace individual User assignment as issue Owner or Assignee.

Backlog

Wiki Page

maps to

Jira

Page

1:1
Fully supported

Backlog Wiki pages are project-scoped and use a custom Backlog wiki markup format. We extract page content, titles, hierarchy (parent-child page relationships), and internal wiki links. Backlog wiki markup is converted to plain text or Jira-supported wiki markup, preserving headings, lists, code blocks, tables, and internal page references. Pages without a clear markup equivalent are flagged in the handoff report for manual review. Jira does not have a native wiki — Confluence is the Atlassian wiki product — so migrated pages land as plain-text or lightly formatted pages in Jira's description and comments fields.

Backlog

Git Repository

maps to

Jira

Repository (Jira Software)

1:1
Fully supported

Backlog Git and Subversion repositories are project-scoped. Repository names, URLs, and the repository description migrate as Jira Software repository references if the destination Jira instance has Jira Software Development panel enabled. The actual source code does not migrate. We document repository URLs and any linked issue keys for the customer's development team to re-establish CI/CD links in their pipeline.

Backlog

Pull Request

maps to

Jira

Pull Request (Jira Software)

1:1
Fully supported

Backlog pull request metadata (title, description, reviewers, status, comments) linked to Git repositories migrates as Jira Development panel data associated with the mapped Jira issue. PR status (Open, Merged, Declined) is preserved as a comment on the Jira issue with PR title and link. Actual diff and code review comments do not migrate. PR-to-issue links are reconstructed using the Backlog issue key embedded in the PR title or description field.

Gotchas + challenges

What specifically takes care here

Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.

Backlog logo

Backlog gotchas

High

Free and Starter tiers enforce hard project-count limits

High

Custom Fields are tier-gated — not available below Premium

Medium

CSV and Excel exports omit full issue descriptions

Medium

API rate limit numbers are not publicly documented

Low

Wiki markup must be converted to destination format

Jira logo

Jira gotchas

High

Unsupported workflow validators silently skipped during migration

High

Custom fields converted to flat text labels when migrating to non-Jira platforms

Medium

Historical status-change timestamps lost when exporting without a Marketplace plugin

Medium

Attachment import failures from oversized files and JQL reference corruption

Medium

Points-based API rate limits enforced on Jira Cloud apps from March 2026

Pair-specific challenges

  • Backlog subtasks use a parent-child model, not a dedicated issue type

    Backlog subtasks are a toggle on a single issue type — the parent issue carries the subtask flag and subtask records are nested under it. Jira uses a dedicated Subtask issue type with its own workflow transitions and issue type scheme. If the Jira project does not have Subtask enabled in its issue type scheme, migrated subtask records will arrive as standard Issues with no link to their parent. We configure the Jira issue type scheme to include Subtask before any record import begins, and we validate the parent link resolves correctly during the sandbox migration. Skipping this step causes subtask data to land as orphan issues.

  • Backlog custom fields do not exist below Premium tier

    Accounts on Backlog Free, Starter, or Standard have no custom fields. Migrating accounts on these tiers will encounter zero custom field definitions during API extraction, which is correct behavior — not an error. We detect the plan tier during discovery and skip the custom field mapping step for accounts below Premium rather than failing or creating empty custom fields. Accounts on Premium or Enterprise have custom fields and we map them to Jira equivalents. The Backlog API does not surface a plan-tier flag directly; we infer it from the presence or absence of the custom fields endpoint response.

  • Jira column status mapping requires explicit board configuration

    Jira boards map status values to columns. Issues migrated with statuses not represented in the board's column configuration will not appear on the board view even though they exist in the project. We configure the Jira project with a workflow that includes the migrated status values before importing records, and we map Backlog status names to Jira status IDs explicitly during the transform step. For teams using Kanban boards in Backlog, we replicate the column-to-status mapping in Jira board configuration. Statuses that have no column mapping are flagged in the reconciliation report.

  • Wiki markup must be converted — no automated Backlog-to-Jira wiki import

    Backlog wikis use a proprietary markup format that Jira's REST API cannot directly consume. We extract wiki page content, headings, lists, code blocks, and internal links, then convert to plain text or Jira-supported wiki markup. Complex Backlog wiki macros (embedded images from specific URLs, custom macros, include directives) that have no Jira equivalent are stripped and listed in the handoff report for manual recreation. Jira's native page storage uses Confluence Storage Format — if the destination includes Confluence, we recommend migrating wiki content there for full formatting fidelity.

  • Backlog API rate limits are undocumented — we probe empirically

    Backlog's API documentation acknowledges rate limits and provides a rate limit status endpoint but does not publish specific request-per-minute or per-hour thresholds. We run a controlled burst of test requests during scoping to measure the 429 response threshold empirically. We set safe batch sizes and mandatory delay intervals for the full export based on that measurement. During migration, if we encounter a 429 response, we apply exponential backoff and retry. This approach prevents mid-migration stalls and ensures all records are extracted without requiring a full restart.

Migration approach

Six steps for a successful Backlog to Jira data migration

  1. Discovery and plan-tier audit

    We audit the Backlog space via the REST API to enumerate all projects, issues, subtasks, milestones, categories, custom fields, users, teams, wikis, and repositories. We detect the plan tier from the presence or absence of the custom fields endpoint response. We count issue and subtask totals, measure API responsiveness to establish batch sizing, and inventory any Backlog Premium features (custom fields, unlimited Gantt view) in use. The discovery output is a written migration scope covering record counts, schema dependencies, and any tier-gated features that require action before migration.

  2. Jira project schema design

    We design the destination Jira project structure before any data moves. This includes creating the Jira Project with the appropriate key, provisioning the issue type scheme (Story, Task, Bug, Subtask enabled), creating the workflow with all migrated status transitions, configuring the Jira board with columns mapped to status values, setting up fix versions (Jira Versions mapped from Backlog Milestones), and adding any custom fields to match the Backlog Premium custom field inventory. All schema design is validated in a Jira Sandbox or test project before production migration begins.

  3. Sandbox migration and reconciliation

    We run a full migration into a Jira Sandbox environment using the full production data volume. The customer reconciles record counts (Projects in, Issues in, Subtasks in, Versions in), spot-checks 25-50 issues across projects against the Backlog source for data accuracy, and validates the subtask hierarchy is intact with correct parent links. The Jira admin confirms board column mapping reflects the migrated status values. Sign-off on the sandbox migration is a precondition for production cutover.

  4. User and group provisioning

    We extract every distinct Backlog user and team referenced as assignee, reporter, or owner across all issues, subtasks, and milestones. Users are matched to Jira accounts by email address. Any Backlog user without a matching Jira account is added to the reconciliation report. Jira Groups are created to match Backlog Teams, and team memberships are preserved. Jira Groups and Users must be provisioned before the record import phase because Jira requires a valid Owner and Assignee reference for each issue.

  5. Production migration in dependency order

    We run the production migration in this sequence: Jira Project and Version creation, then Issues (parent records first), then Subtasks with parent ID resolution, then custom fields (Premium accounts only), then labels, then attachments (by URL reference), then Git PR metadata as Jira Development panel comments, then wiki content as Jira page descriptions. Each phase emits a row-count reconciliation report. If the migration is interrupted, we resume from the last completed phase using Jira issue keys as the dedupe anchor rather than reprocessing completed records.

  6. Cutover, validation, and automation handoff

    We freeze Backlog writes during the cutover window, run a final delta scan for any records modified during migration, then mark Jira as the system of record. We deliver a written inventory of all Backlog workflow configurations, automation rules, and notification settings requiring rebuild in Jira. We do not rebuild these as Jira workflows, automation rules, or board filters — that is an admin task or a separate engagement. We support a three-business-day hypercare window to resolve data reconciliation issues raised by the team after cutover.

Platform deep dives

Context on both ends of the pair

Backlog logo

Backlog

Source

Strengths

  • No per-user pricing — costs scale with storage and project count, not headcount.
  • Integrated Git and Subversion with issue linking, pull requests, and code review.
  • Free plan includes full issue tracking with 1 project and 10 users — genuine no-cost option.
  • Gantt charts, burndown charts, and issue templates available on Standard plan.
  • SAML SSO and advanced security controls available on the Enterprise tier.

Weaknesses

  • Reporting and analytics are described as weak — limited dashboarding compared to modern PM tools.
  • Custom fields are locked behind the Premium tier, limiting lower-tier migrations.
  • No public documentation of specific API rate limit numbers.
  • Visual design and UI is considered dated by some reviewers.
  • Custom object types beyond Issues are not supported — Backlog is not configurable for non-standard data models.
Jira logo

Jira

Destination

Strengths

  • Deeply customizable workflows and status schemes with no hard limits on workflow complexity or number of custom statuses.
  • Strong agile ceremony support: sprint planning, backlog grooming, velocity tracking, and burndown charts for Scrum teams.
  • Industry-standard developer tool with native Git integration linking commits, pull requests, and deployments to issues.
  • Large Atlassian Marketplace with thousands of plugins extending time tracking, portfolio management, and reporting capabilities.
  • Free tier available for up to 10 users with unlimited issues, enabling evaluation before committing to a paid plan.

Weaknesses

  • Excessive configurability creates a steep learning curve; cross-team consistency is hard to maintain without strict governance.
  • Performance degrades with large backlogs, complex custom fields, and heavily nested issue hierarchies.
  • Reporting requires additional configuration or paid plugins; out-of-the-box analytics are limited for business users.
  • Jira lacks native sprint management, requiring Jira Software for true agile team features.
  • Teams outside engineering resist adoption due to UI complexity, leaving the all-in-one promise unfulfilled for cross-functional organizations.

Complexity grading

How hard is this migration?

Standard Project Management migration. 3 of 8 objects need a mapping; the rest are 1:1.

B

Overall complexity

Standard migration

Derived from compatibility, mapping clarity, API constraints, and data volume across Backlog and Jira.

  • Object compatibility

    B

    3 of 8 objects need a mapping; the rest are 1:1.

  • Field mapping clarity

    C

    Field mapping is derived from defaults — final spec confirmed during the sample migration.

  • Timeline complexity

    B

    8-object category — typical timelines run 2–7 days end-to-end.

  • API constraints

    B

    Backlog: Per-minute, per-user limits that vary by plan (Free vs Paid) and by request type; exact numbers are dynamic and exposed via the GET /api/v2/rateLimit endpoint.

  • Data volume sensitivity

    A

    Backlog exposes a bulk API — large-volume migrations stream efficiently.

Estimator

Estimate your Backlog to Jira migration cost

Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.

Step 1

What are you migrating?

Pick a category, then your source and destination platforms.

Category

FAQ

Frequently asked questions about Backlog to Jira data migrations

Answers to the questions buyers ask most during Backlog to Jira migration scoping. Not seeing yours? Book a call.

Can't find your answer?

Walk through your Backlog to Jira migration with a real engineer — 30 minutes, free, written quote within 24 hours.

Book a free 30 minute consultation

Straightforward migrations under 10 projects and 15,000 issues typically complete in two to four weeks. Migrations with custom fields on Premium accounts, large wiki libraries, Git pull request metadata, or high subtask ratios (more than two subtasks per issue on average) extend to five to eight weeks because of custom field type mapping, wiki markup conversion, and subtask hierarchy validation. Jira Software Cloud has pre-migration check phases that add hours to the overall timeline for larger instances.

Adjacent paths

Related migrations to explore

Ready when you are

Move from Backlog.
Land in Jira, intact.

Tell us record counts and timeline. We'll come back with a written quote inside 1 business day — no commitment, no sales pitch.

Accuracy guarantee Rollback included Quote in 1 business day