Project Management migration

Migrate from Ganttic to Jira

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

Ganttic logo

Ganttic

Source

Jira

Destination

Jira logo

Compatibility

90%

9 of 10

objects map 1:1 between Ganttic and Jira.

Complexity

BStandard

Timeline

3-5 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Ganttic to Jira is a conceptual shift from a resource-centric to an issue-centric data model. Ganttic treats Resources as the primary planning entity with Projects and Tasks as subordinate scheduling containers; Jira treats Issues as the primary entity with Projects providing configuration context. We resolve this structural difference during scoping by mapping Ganttic Resources to Jira Users (for human assignees) and to custom field values (for equipment, rooms, and facilities), and by mapping Ganttic Projects directly to Jira Projects with their Task hierarchy preserved as Jira issue types. Ganttic's nine Data Field types require pre-seeding in Jira before any records import; List and Multi-Select fields must have their picklist values created first or imports fail validation. Ganttic's undocumented API rate limits mean we implement adaptive throttling with exponential backoff and recommend CSV fallback for bulk record creation. Jira Workflows, Jira Automation rules, and Ganttic's Custom Views do not migrate; we deliver a written inventory of each for the customer's admin to rebuild post-migration.

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

Ganttic logo

Ganttic

What's pushing teams away

  • The user interface is described as clumsy by some reviewers, making navigation unintuitive compared to competitors like Wrike
  • Limited review volume (29 G2 reviews) makes it hard to gauge long-term satisfaction and support quality before committing
  • Teams outgrow Ganttic as they scale and need stronger integrations, advanced reporting, or enterprise features not fully available
  • API documentation is sparse and rate limits are not publicly documented, creating friction for automated workflows and migration tooling
  • Mid-market focus means large enterprises with complex org structures find the platform insufficient for their needs

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 Ganttic objects map to Jira

Each row shows how a Ganttic 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.

Ganttic

Resource

maps to

Jira

User (people) or Custom Field (equipment, rooms, facilities)

1:many
Fully supported

Ganttic Resources are typed as people, rooms, vehicles, equipment, or custom asset categories. Human Resources with email addresses map to Jira User accounts. Non-human Resources (equipment, rooms, vehicles, facilities) do not have a native Jira equivalent; we model them as Jira custom field values using a single-select or multi-select custom field with the resource names as options. This requires pre-seeding the picklist before Task import so that assignee and resource allocation fields validate correctly.

Ganttic

Resource Grouping

maps to

Jira

Jira Group or Custom Field

1:1
Mapping required

Ganttic Resources can be grouped by any Data Field value, creating nested group hierarchies. We preserve these hierarchies by mapping top-level groups to Jira Groups and sub-groups to a custom field on the User record. If the grouping logic references non-human Resources, we use a cascading custom field structure instead.

Ganttic

Project

maps to

Jira

Project

1:1
Fully supported

Ganttic Projects map directly to Jira Projects. We preserve Project name, description, start and end dates, and the full Data Field set. The Ganttic Project time period (start/end dates) maps to the Jira Project's start date and the default fix version target date. If multiple Ganttic Projects map to a single Jira Project, we create Jira issue type schemes to separate the data while sharing configuration.

Ganttic

Task

maps to

Jira

Issue (Story, Task, Bug)

1:1
Fully supported

Ganttic Tasks map to Jira Issues with issue type determined during scoping. Tasks with deliverables map to Stories; Tasks with discrete actions map to Tasks; Tasks flagged as blockers or quality items map to Bugs. We preserve Task start/end dates, assignees (resolved via the resource-to-user mapping), and all Data Field values. Parent-child Task relationships in Ganttic map to Jira sub-task links or Jira Issue Hierarchy.

Ganttic

Milestone

maps to

Jira

Fix Version

1:1
Fully supported

Ganttic Milestones are implemented as date-type Data Fields on Projects rather than a distinct object. We convert them to Jira Fix Versions (Releases) with the milestone name as the version name and the milestone date as the release date. If a Ganttic Project has multiple milestones, we create one Fix Version per milestone and link related Issues using the Fix Version field.

Ganttic

Project Data Field

maps to

Jira

Custom Field

1:1
Fully supported

Ganttic Project-level Data Fields map to Jira Project-level custom fields. The nine Ganttic Data Field types map to Jira equivalents: List maps to Select, Multi-Select maps to Multi-Select, Number maps to Number, Text maps to Text Field, Date maps to Date Picker. We pre-create the custom field in Jira during schema design and assign it to the relevant Issue Type Scheme so it appears on the correct issue types.

Ganttic

Task Data Field

maps to

Jira

Custom Field

1:1
Fully supported

Ganttic Task-level Data Fields follow the same nine-type system as Projects and Resources. We perform type-aware mapping and flag any task fields marked as mandatory in Ganttic to ensure required validation is enforced in Jira. List and Multi-Select picklist values must be pre-seeded in Jira before record import; we generate a pre-migration seed script for these fields during discovery.

Ganttic

Resource Data Field

maps to

Jira

Custom Field on User or Issue

1:1
Fully supported

Resource Data Fields store custom information like department, skillset, location, or role. Human Resource Data Fields migrate as custom fields on the Jira User record (if Jira Data Center or Server with User Management enabled) or as custom fields on Issues. Non-human Resource Data Fields migrate as custom fields on the Jira Issues they relate to, preserving the resource's custom attributes in the destination system.

Ganttic

Custom View

maps to

Jira

Saved Filter + Board

1:1
Fully supported

Ganttic Custom Views define per-view time periods, groupings, and filtering criteria. We export View configurations during discovery and map them to Jira Saved Filters (JQL queries capturing the same filter logic) and Jira Boards (Kanban or Scrum). The time period and grouping logic may require adjustment because Jira's time-based filtering uses different primitives (sprint dates, fix version dates) than Ganttic's timeline windows.

Ganttic

Report

maps to

Jira

Dashboard Gadget

1:1
Fully supported

Ganttic Reports export as CSV or PDF during discovery. We extract calculated metrics and summaries from CSV exports and map them to Jira Dashboard Gadgets (pie charts, bar charts, statistics gadgets) where structurally equivalent. Any report that exists only in a Ganttic view (calculated in real time, not stored as data) is flagged as a non-migratable artifact and listed in the handoff document for the customer's admin to rebuild as a Jira Dashboard.

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.

Ganttic logo

Ganttic gotchas

Medium

Data Field type mapping requires pre-seeded picklist values

Low

Resource-based pricing means only active resources cost money

Medium

Project shifting cannot be automatically reversed

High

API rate limits are not publicly documented

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

  • Ganttic Data Field picklist values must be pre-seeded in Jira

    Ganttic's nine Data Field types include List and Multi-Select fields that function as dropdowns with custom value sets. Jira's custom field validation rejects any record import where a picklist value does not already exist in the target field. We extract all List and Multi-Select values during discovery, generate a pre-migration seed script that creates the options in Jira before any record import begins, and validate that the import succeeds on the picklist validation step. Skipping this step results in silent record failures or rejection on the first bulk import attempt.

  • Ganttic API rate limits are undocumented

    Ganttic's Help Center documents API endpoints but does not publish rate limits or quota thresholds. A large import job could hit undocumented throttling and fail silently. We implement adaptive throttling with exponential backoff on all Ganttic API calls, starting conservatively and ramping only when we observe actual response headers. We also recommend CSV export from Ganttic as the primary bulk data extraction path for record counts over 1,000, bypassing API rate uncertainty for data retrieval while using the API only for schema discovery and delta sync.

  • Non-human Resources have no native Jira equivalent

    Ganttic Resources can represent people, rooms, vehicles, equipment, or any custom asset type. Jira's native model only supports human Users. Equipment, rooms, and facilities require custom field modeling using select or multi-select fields with the resource names as options. If a team uses Ganttic's resource allocation feature to schedule non-human assets against Tasks (e.g., booking a vehicle for a project), that scheduling relationship does not map to Jira's assignee field and must be captured as a separate custom field with manual interpretation by the customer's team post-migration.

  • Jira Workflows and Ganttic Custom Views do not migrate

    Ganttic Custom Views and Jira Workflows are both configuration artifacts that do not carry over in data migration. We export Ganttic View definitions (filter logic, grouping, time period settings) and Jira Workflow configurations (statuses, transitions, validators, post-functions) as part of discovery and deliver them in a written inventory with a field-by-field mapping recommendation. The customer's Jira admin rebuilds views as Saved Filters and Boards, and workflows are redesigned in Jira's workflow editor or exported as XML for a partner to import.

  • Ganttic Project shift operations cannot be automatically reversed

    Ganttic's shift feature moves an entire Project along with its Tasks and Milestones along the timeline. The documentation states this action cannot be automatically reverted; it must be undone Task by Task manually. When migrating project dates to Jira, we capture the full pre-shift state of all affected records during discovery so the customer's Ganttic instance remains undisturbed during parallel-run validation. Jira's Fix Version dates and sprint date ranges are set independently of issue dates, which provides natural reversal capability that Ganttic lacks.

Migration approach

Six steps for a successful Ganttic to Jira data migration

  1. Discovery and resource type audit

    We audit the Ganttic instance across Resources (with type classification: human, equipment, room, vehicle, facility), Projects, Tasks, Milestones, Data Fields (with field type and visibility rules), Custom Views, and Reports. We classify every Resource by type and flag non-human Resources as requiring custom field modeling in Jira. We export all List and Multi-Select picklist values for pre-seeding and capture Jira project configuration requirements (issue type scheme, workflow, field configuration). The discovery output is a written migration scope with resource type classification, Data Field mapping matrix, and Jira edition recommendation.

  2. Jira schema design and custom field pre-seeding

    We design the Jira destination schema in a Sandbox environment. This includes creating Projects with appropriate issue type schemes, creating custom fields for every Ganttic Data Field with type-mapped Jira field types, pre-seeding all List and Multi-Select picklist options, creating Fix Versions for each Ganttic Milestone, and designing the resource allocation custom field for non-human Resources. We implement adaptive throttling on Ganttic API calls and prepare the CSV export pipeline for bulk data extraction. Schema is validated in Sandbox before any data moves to production.

  3. Sandbox migration and reconciliation

    We run a full migration into the Jira Sandbox using production-like data volume. The customer's project manager and Jira admin reconcile record counts (Resources mapped, Projects in, Tasks in, Milestones as Fix Versions), spot-check 20-40 random Tasks against Ganttic source data (dates, assignees, Data Field values), and validate that non-human Resource custom fields render correctly. Any mapping corrections happen in Sandbox before production migration begins.

  4. Resource-to-User mapping and Jira User provisioning

    We extract every distinct Ganttic Resource with an email address and match by email against the Jira destination instance's User table. Human Resources without Jira User accounts go to a reconciliation queue for the customer's Jira admin to provision before record import. Non-human Resources are captured in the resource custom field with their Ganttic names as picklist values. Migration cannot proceed to Task import until the resource-to-user mapping is validated because assignee fields must reference valid Jira Users.

  5. Production migration in dependency order

    We run production migration in record-dependency order: Jira Users (manual provisioning validated), Jira Projects (with issue type schemes and field configurations), Fix Versions (from Ganttic Milestones), Tasks (with assignee resolution, Data Field values, and parent-child links), Resource custom field values for non-human Resources, and Custom Views exported as Saved Filters and Board configurations. Each phase emits a row-count reconciliation report before the next phase begins. We use adaptive throttling with exponential backoff on all Ganttic API calls and CSV export as the primary bulk extraction path.

  6. Cutover, validation, and configuration rebuild handoff

    We freeze Ganttic writes during cutover, run a final delta migration of any records modified during the migration window, then enable Jira as the system of record. We deliver the Custom View inventory, Workflow rebuild recommendations, and Data Field mapping document to the customer's Jira admin team. We support a one-week hypercare window where we resolve any reconciliation issues raised by the team. We do not rebuild Ganttic Custom Views as Jira Boards or Workflows inside the migration scope; that is a separate engagement or an internal admin task.

Platform deep dives

Context on both ends of the pair

Ganttic logo

Ganttic

Source

Strengths

  • Resource-based pricing aligns cost with actual usage — archived resources do not count toward billing
  • Unlimited users across all plans means no per-seat cost friction when scaling teams
  • Flexible Data Field system with nine types and no required fields suits diverse industries
  • Visual Gantt scheduling with drag-and-drop makes capacity conflicts easy to spot
  • CSV import and export for Resources, Tasks, Projects, and Data Fields supports data portability

Weaknesses

  • Sparse public API documentation and undocumented rate limits complicate automated migrations
  • Clumsy UI reported by some reviewers; less intuitive than competitors like Wrike
  • Small review volume (29 G2 reviews) makes it difficult to assess support quality reliably
  • Limited enterprise feature set causes some mid-market teams to outgrow the platform
  • Shift operations (moving project timelines) cannot be automatically reverted in Ganttic
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 Ganttic 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

    Ganttic: Not publicly documented.

  • Data volume sensitivity

    B

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

Estimator

Estimate your Ganttic 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 Ganttic to Jira data migrations

Answers to the questions buyers ask most during Ganttic 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 500 Resources, 50 Projects, and 2,000 Tasks with straightforward human-resource-only mapping. Migrations with non-human Resources (equipment, rooms, facilities requiring custom field modeling), complex Data Field hierarchies with hundreds of picklist options, or multi-Ganttic-project consolidation into a single Jira instance move to seven to ten weeks because of resource-type mapping design, picklist pre-seeding, and Jira schema validation in Sandbox.

Adjacent paths

Related migrations to explore

Ready when you are

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