Project Management migration

Migrate from TeamGantt to Jira

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

TeamGantt logo

TeamGantt

Source

Jira

Destination

Jira logo

Compatibility

67%

8 of 12

objects map 1:1 between TeamGantt and Jira.

Complexity

BStandard

Timeline

3-5 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from TeamGantt to Jira is a philosophical shift from Gantt-first visual scheduling to issue-centric work management. TeamGantt uses Projects as top-level containers with Tasks that carry start dates, durations, and explicit dependency chains visible on a drag-and-drop timeline. Jira uses Projects containing Issues (Epic, Story, Task, Bug) where scheduling is handled by the Advanced Roadmaps add-on and dependency links are maintained through the Issue Links field or the Dependencies field in Advanced Roadmaps. We map TeamGantt task groups to Jira Epics and Stories, preserve Finish-to-Start and Start-to-Start dependency relationships as Jira Issue Links (Blocks/Is blocked by), and carry milestone dates as Jira Milestone-type issue links. Baseline snapshots from TeamGantt are written to a migration artifact so that the customer's admin can configure Advanced Roadmaps baselines manually post-migration. TeamGantt automations and templates do not migrate; we deliver a written inventory of these for the admin to rebuild in Jira's workflow editor.

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

TeamGantt logo

TeamGantt

What's pushing teams away

  • Teams report that resource management is limited—workload views are paywalled behind Pro and the capacity planning features are basic compared to dedicated resource management tools.
  • The lack of a native macOS desktop app frustrates users who want a full-screen experience; the iPad/iPhone app is described as small and insufficient for complex project management.
  • Integration ecosystem is narrow—Zapier is the primary no-code integration path, and teams needing native bi-directional sync with tools like Salesforce or QuickBooks find themselves building custom API workarounds.
  • Some teams find collaboration features lacking—particularly threaded discussions, @mentions, and shared document editing that modern PM tools bundle in.
  • As teams scale beyond 5–10 concurrent projects, the per-project pricing model becomes expensive and teams report looking for unlimited-project plans or portfolio-level views that TeamGantt Basic and Standard do not offer.

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 TeamGantt objects map to Jira

Each row shows how a TeamGantt 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.

TeamGantt

Project

maps to

Jira

Project

1:1
Fully supported

TeamGantt Projects map directly to Jira Projects. The TeamGantt project name becomes the Jira Project name; the TeamGantt project description maps to the Jira Project Description field. Project key prefix (e.g., TG or PROJ) must be defined before migration because Jira requires a 2-10 character uppercase prefix on all issue keys. TeamGantt project start date (derived from the earliest task) is set as the Jira Project lead date or recorded as a custom field for Advanced Roadmaps anchor configuration.

TeamGantt

Task

maps to

Jira

Story or Task (issue type)

1:many
Fully supported

TeamGantt tasks map to Jira Story or Task issue types depending on the parent Group relationship. Tasks with no children map to Jira Story (if representing deliverable work) or Task (if representing action items). Jira's Assignee, Priority, Due Date, and Description fields map directly from TeamGantt task fields. The Jira issue Status (To Do, In Progress, Done) is set based on the TeamGantt task percent_complete value: 0% = To Do, 1-99% = In Progress, 100% = Done. Jira sub-tasks are used for TeamGantt Groups with children, where each sub-group becomes a Jira sub-task issue.

TeamGantt

Group (Subtask hierarchy)

maps to

Jira

Epic or Sub-task

1:many
Fully supported

TeamGantt task Groups (nested subtasks) require a two-level mapping. Top-level groups map to Jira Epic issues within the Project, with the Epic's summary set to the group name and the Epic description carrying the group's notes. Nested sub-tasks within a Group map to Jira Story or Task issues linked as children to the parent Epic. The Jira Epic Link custom field (or the parent-link in Advanced Roadmaps) connects each Story to its parent Epic. Teams that do not use Epics configure Stories instead and use Jira's parent-link field for hierarchy.

TeamGantt

Milestone

maps to

Jira

Milestone (Advanced Roadmaps) or Issue with zero duration

lossy
Fully supported

TeamGantt milestones are zero-duration date markers. In Jira Standard (no Advanced Roadmaps), we map milestones to Jira Task issues with a custom field milestone_date__c set to the original date, and a label milestone applied. In Jira Premium/Enterprise with Advanced Roadmaps enabled, we create Jira Milestone records linked to the relevant Epic or parent Story. The milestone name and target date migrate; no completion percentage is carried since TeamGantt milestones are static markers.

TeamGantt

Dependency (Finish-to-Start, Start-to-Start)

maps to

Jira

Issue Link (Blocks / is blocked by)

1:1
Fully supported

TeamGantt Finish-to-Start dependencies map to Jira Issue Links of type Blocks. If Task B depends on Task A (Finish-to-Start), Jira Issue B gets a link of type Blocks pointing to Jira Issue A. Start-to-Start dependencies map to Jira Issue Links of type 'is dependent on' (a bidirectional relationship). We preserve the dependency type and lag time (if any) in a custom field dependency_type__c on the linked issues. Jira requires the destination project to have Issue Links enabled in Project Settings > Issue Features before migration. Lag time is recorded as days_offset__c on each linked issue.

TeamGantt

Baseline

maps to

Jira

Migration artifact + Advanced Roadmaps baseline (Premium/Enterprise)

1:1
Fully supported

TeamGantt baselines capture a snapshot of the original planned start and end dates for tasks. Jira Advanced Roadmaps (Premium/Enterprise) supports baseline views. We export all saved TeamGantt baselines as a structured JSON artifact (baseline_name, issue_key, planned_start, planned_end, actual_start, actual_end) and provide post-migration instructions for the admin to configure Advanced Roadmaps baselines from this artifact. Standard-tier Jira migrations store baseline data as a custom field set on each migrated issue so the original planned dates are visible without the Advanced Roadmaps add-on.

TeamGantt

User

maps to

Jira

User

1:1
Fully supported

TeamGantt user records (name, email, role) map to Jira User accounts. We resolve users by email address against the Jira Cloud destination org. The TeamGantt role (Manager, Collaborator, Guest) maps to a Jira project role (Administrators, Members, Viewers). If the Jira destination has fewer seats than the TeamGantt user count, we flag users not provisioned in Jira and provide a migration-user selection matrix so the admin chooses which users to carry forward.

TeamGantt

Label

maps to

Jira

Label

1:1
Fully supported

TeamGantt labels are categorical tags applied to tasks for grouping. These map directly to Jira Labels (available in all Jira tiers). The TeamGantt label name becomes the Jira Label text value. Labels are applied to the migrated Jira issue as a Label field entry. Jira Labels are not hierarchical; if TeamGantt labels use a hierarchical naming convention (e.g., Dept:Subdept:TaskType), we flatten them to Jira Label format and document the original structure in the mapping spec.

TeamGantt

Checklist

maps to

Jira

Checklist (Jira issue description) or Sub-task

lossy
Fully supported

TeamGantt checklist items on tasks are migrated as Jira Checklist app items if the destination org has the native Jira Checklist for issue subtasks (Atlassian-owned, available on Premium) or as structured text appended to the Jira issue Description if the destination does not have the Checklist app. We read checklist completion status (checked/unchecked) from TeamGantt and apply the same state in Jira. The mapping choice is made during scoping based on the destination's installed apps.

TeamGantt

Discussion (Task comments)

maps to

Jira

Comment

1:1
Fully supported

TeamGantt discussion threads on tasks map to Jira Issue Comments. We preserve full comment text, author attribution (resolved to Jira User by email), and timestamp (ActivityDate set to the original TeamGantt comment date). Comment threading structure is flattened in Jira because Jira Comments are a flat list; parent-child relationships in TeamGantt discussions are documented as a note in the mapping spec. Mentions in TeamGantt comments (@user references) are preserved as plain text and mapped to Jira user mentions where the Jira user account exists.

TeamGantt

Custom Field (Project level)

maps to

Jira

Custom Field

1:1
Fully supported

TeamGantt custom fields at the project level map to Jira Project-level custom fields. We discover field types via the TeamGantt API (text, number, date, dropdown) and create equivalent Jira custom fields before migration. Text fields map to Jira Text Field (free-text). Number fields map to Jira Number Field. Date fields map to Jira Date Picker. Dropdown fields map to Jira Select List (single choice) or Radio Button depending on the TeamGantt field configuration. Custom field values are set on the Jira Project or on each migrated issue as appropriate.

TeamGantt

Custom Field (Task level)

maps to

Jira

Custom Field

1:1
Fully supported

TeamGantt task-level custom fields map to Jira issue-level custom fields. We handle type mismatches by creating the closest Jira equivalent (e.g., multi-select from TeamGantt becomes a Jira Labels field or multi-select custom field if Jira Multi-Select is available). Currency fields from TeamGantt map to Jira Number Field. URL fields map to Jira URL Field. All custom field definitions (name, type, options, applicable issue types) are documented in the mapping spec with Jira configuration steps for the admin to verify before production migration.

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.

TeamGantt logo

TeamGantt gotchas

High

Project billing model charges per project on Basic tier

Medium

Workloads report requires Pro or Unlimited plan

Medium

Free plan exports are limited to CSV with no API access

Low

Project start date is inferred, not set explicitly

Low

Time zone and language handling for non-Latin characters

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

  • TeamGantt baseline snapshots do not map to Jira baselines automatically

    Jira's baseline functionality is available only in Advanced Roadmaps (Jira Premium/Enterprise at $16/user/month). Jira Standard does not include baseline support. We export TeamGantt baseline data as a structured JSON artifact and provide post-migration instructions for the admin to create Advanced Roadmaps baselines manually from this artifact. If the destination Jira org is on Standard, baseline data is stored as custom fields on each migrated issue so planned vs. actual dates remain visible but do not appear in a dedicated baseline comparison view.

  • Dependency lag time requires a custom field in Jira

    TeamGantt supports Finish-to-Start and Start-to-Start dependency types with explicit lag-time values (positive or negative days offset). Jira's standard Issue Links (Blocks / is blocked by) do not natively carry a lag-time field. We store the original TeamGantt lag time as a custom field days_offset__c on the linked Jira issue. Jira Advanced Roadmaps handles lag time natively in its dependency field; for Standard-tier destinations, the custom field provides a manual reference for the admin to apply offset dates in Jira.

  • Jira's Gantt chart requires Advanced Roadmaps or a Marketplace add-on

    TeamGantt's primary interface is a Gantt chart with drag-and-drop rescheduling. Jira's native board and backlog views do not display a Gantt chart. Jira Advanced Roadmaps (Premium/Enterprise) provides a timeline/Gantt view with dependency visualization, but it is a separate configuration step after migration. Teams that rely on the Gantt view for stakeholder reporting must either upgrade to Jira Premium for Advanced Roadmaps or install a Gantt-chart Marketplace app (e.g., Structure, WBS Gantt-Chart, BigGantt). We document the recommended configuration path for timeline parity during migration scoping.

  • TeamGantt's Workloads report is Pro/Unlimited-only and may be incomplete

    If the source TeamGantt account is on Basic or Standard tier, the Workloads report is not accessible via the UI and workload data must be sourced from the CSV export. CSV export includes task assignments but may not include hours-per-week allocation values that Workloads provides. We flag any tasks where workload allocation is missing from the export and note them in the mapping spec. Jira's capacity planning (available in Advanced Roadmaps Premium/Enterprise) is configured post-migration by mapping the TeamGantt workload allocation to Jira User capacity settings.

  • Jira issue keys must be defined before migration starts

    Jira requires a project key prefix (2-10 uppercase characters) before any issues can be created. TeamGantt uses project names but no key prefix system. We coordinate with the customer during scoping to define Jira Project keys, and these must be committed in Jira before migration begins. If the customer changes the project key after migration starts, Jira's internal ID references break and re-import becomes necessary. We validate the project key format during the pre-migration audit.

Migration approach

Six steps for a successful TeamGantt to Jira data migration

  1. Discovery and Jira edition assessment

    We audit the TeamGantt account across plan tier (Free/Basic/Standard/Pro/Unlimited), project count, task volume, dependency chain complexity, baseline count, and custom field inventory. We pair this with a Jira edition assessment: Standard ($8.15/user, min 10 users) covers most migrations; Premium ($16/user) is required if the customer needs Advanced Roadmaps for timeline parity, baseline views, or capacity planning. We also verify whether the Jira destination org already exists or needs provisioning, and we identify the project key prefix to use.

  2. Schema design and Advanced Roadmaps configuration plan

    We design the destination Jira project structure: issue type scheme (Epic/Story/Task/Bug/Sub-task), custom fields (matching TeamGantt custom field types to Jira field types), labels (mapped from TeamGantt label names), and issue link types (Blocks / is blocked by enabled). If the destination is Premium/Enterprise, we include the Advanced Roadmaps configuration steps for the admin to enable the timeline view and configure baselines post-migration. If the destination is Standard, we document the custom field approach for planned-date visibility. Jira project schema is configured in a Sandbox first for validation before production migration.

  3. CSV + API extraction from TeamGantt

    We extract TeamGantt data via the REST API for accounts on Standard/Pro/Unlimited tiers (where API access is available) and via CSV export for Free-tier accounts or when API access is blocked. We cross-reference CSV and API data to reconcile discrepancies in task dates, assignees, and completion percentages. The Workloads report is requested from the API (Pro/Unlimited) with CSV fallback for Basic/Standard. All TeamGantt baseline snapshots are exported as structured JSON. The extraction output is a staging dataset in our migration tool with full lineage metadata for reconciliation.

  4. Sandbox migration and reconciliation

    We run a full migration into the Jira destination Sandbox using production-like data volume. The customer's project manager and Jira admin reconcile record counts (Projects in, Epics/Stories/Tasks in, sub-tasks in, dependencies in, milestones in), spot-check 25-50 random Jira issues against the TeamGantt source, and verify that labels, assignees, and dates are correctly mapped. Any mapping corrections (custom field type mismatches, issue type assignment errors, label flattening issues) are resolved in this phase. The admin approves the mapping spec before production migration begins.

  5. Production migration in dependency order

    We run production migration in record-dependency order: Jira Project (created first with the agreed key prefix), Jira Issue Types and custom fields (schema deployed via Jira REST API), Epics (from TeamGantt Groups), Stories and Tasks (from TeamGantt Tasks, with parent Epic linkage), Sub-tasks (from nested TeamGantt Groups), Issue Links (dependency chains as Blocks links with days_offset__c), Labels (applied to all issues), Comments (preserving author, timestamp, and thread ordering), and Custom Field values. Each phase emits a row-count reconciliation report before the next phase begins.

  6. Cutover, validation, and automations handoff

    We freeze TeamGantt writes during cutover and run a final delta migration of any tasks modified during the migration window. We then enable Jira as the system of record and disable write access to TeamGantt to prevent divergence. We deliver the TeamGantt Automations inventory document (listing every automation rule by trigger and action) and the Advanced Roadmaps configuration runbook to the customer's Jira admin. We do not rebuild TeamGantt automations as Jira Automation rules inside the migration scope; that is a separate engagement. We support a one-week hypercare window for reconciliation issues raised during the first production week.

Platform deep dives

Context on both ends of the pair

TeamGantt logo

TeamGantt

Source

Strengths

  • Drag-and-drop Gantt chart scheduling with automatic dependency propagation and rescheduling notifications.
  • Generous free tier with unlimited tasks and projects, no time cap, making it accessible for freelancers and small teams.
  • Task-level time tracking with hourly estimation and a dedicated Workloads report on higher plans.
  • Baseline comparison that lets teams see planned vs. actual progress over time.
  • Clean CSV and PDF export for sharing project data outside the platform.

Weaknesses

  • No native macOS desktop app; the iOS app is a scaled mobile interface, not a full desktop client.
  • Per-project pricing on lower tiers becomes costly for teams managing many concurrent projects.
  • Resource management is limited—workload views are gated behind Pro/Unlimited, and advanced capacity planning features are absent.
  • Collaboration features are basic; no native document co-editing or rich @mention notification system within tasks.
  • Limited integrations beyond Zapier; no native bi-directional sync with major CRMs or accounting tools.
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 TeamGantt 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

    TeamGantt: Not publicly documented.

  • Data volume sensitivity

    B

    TeamGantt doesn't expose a bulk API — REST + parallelization used for high-volume runs.

Estimator

Estimate your TeamGantt 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 TeamGantt to Jira data migrations

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

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Most migrations land between three and five weeks for accounts under 5,000 tasks and 20 projects without Advanced Roadmaps configuration. Migrations requiring Advanced Roadmaps (Jira Premium) for timeline parity, large baseline artifacts, or complex subtask hierarchies exceeding 50 levels move to eight to twelve weeks because of Advanced Roadmaps configuration, Jira Automation inventory documentation, and Jira Cloud Migration Assistant pre-flight handling. Jira itself does not have a native TeamGantt import tool; FlitStack AI uses the Jira REST API directly.

Adjacent paths

Related migrations to explore

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