Project Management migration
Field-level mapping, validation, and rollback between Ganttic and Jira. We move data and schema; workflows are rebuilt natively in Jira.
Ganttic
Source
Jira
Destination
Compatibility
9 of 10
objects map 1:1 between Ganttic and Jira.
Complexity
BStandard
Timeline
3-5 weeks
Overview
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.
Every standard and custom field arrives verified.
AI proposes the map; you confirm before any record moves.
Parent–child, lookups, and ownership stay linked.
Calls, emails, meetings — with original timestamps.
Documents, uploads, and inline notes move with the record.
Why teams make this switch
Leaving
What's pushing teams away
Choosing
What's pulling them in
Object mapping
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
Jira
User (people) or Custom Field (equipment, rooms, facilities)
1:manyGanttic 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
Jira
Jira Group or Custom Field
1:1Ganttic 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
Jira
Project
1:1Ganttic 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
Jira
Issue (Story, Task, Bug)
1:1Ganttic 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
Jira
Fix Version
1:1Ganttic 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
Jira
Custom Field
1:1Ganttic 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
Jira
Custom Field
1:1Ganttic 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
Jira
Custom Field on User or Issue
1:1Resource 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
Jira
Saved Filter + Board
1:1Ganttic 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
Jira
Dashboard Gadget
1:1Ganttic 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.
| Ganttic | Jira | Compatibility | |
|---|---|---|---|
| Resource | User (people) or Custom Field (equipment, rooms, facilities)1:many | Fully supported | |
| Resource Grouping | Jira Group or Custom Field1:1 | Mapping required | |
| Project | Project1:1 | Fully supported | |
| Task | Issue (Story, Task, Bug)1:1 | Fully supported | |
| Milestone | Fix Version1:1 | Fully supported | |
| Project Data Field | Custom Field1:1 | Fully supported | |
| Task Data Field | Custom Field1:1 | Fully supported | |
| Resource Data Field | Custom Field on User or Issue1:1 | Fully supported | |
| Custom View | Saved Filter + Board1:1 | Fully supported | |
| Report | Dashboard Gadget1:1 | Fully supported |
Gotchas + challenges
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 gotchas
Data Field type mapping requires pre-seeded picklist values
Resource-based pricing means only active resources cost money
Project shifting cannot be automatically reversed
API rate limits are not publicly documented
Jira gotchas
Unsupported workflow validators silently skipped during migration
Custom fields converted to flat text labels when migrating to non-Jira platforms
Historical status-change timestamps lost when exporting without a Marketplace plugin
Attachment import failures from oversized files and JQL reference corruption
Points-based API rate limits enforced on Jira Cloud apps from March 2026
Pair-specific challenges
Migration approach
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.
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.
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.
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.
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.
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
Ganttic
Source
Strengths
Weaknesses
Jira
Destination
Strengths
Weaknesses
Complexity grading
Standard Project Management migration. 3 of 8 objects need a mapping; the rest are 1:1.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Ganttic and Jira.
Object compatibility
3 of 8 objects need a mapping; the rest are 1:1.
Field mapping clarity
Field mapping is derived from defaults — final spec confirmed during the sample migration.
Timeline complexity
8-object category — typical timelines run 2–7 days end-to-end.
API constraints
Ganttic: Not publicly documented.
Data volume sensitivity
Ganttic doesn't expose a bulk API — REST + parallelization used for high-volume runs.
Estimator
Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.
Step 1
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