CRM migration
Field-level mapping, validation, and rollback between Spark CRM and Twenty CRM. We move data and schema; workflows are rebuilt natively in Twenty CRM.
Spark CRM
Source
Twenty CRM
Destination
Compatibility
12 of 12
objects map 1:1 between Spark CRM and Twenty CRM.
Complexity
BStandard
Timeline
48–72 hours
Overview
Spark CRM is an email-first contact management tool that stores contacts, companies, deals, and activities primarily around email engagement data. Twenty CRM is an open-source relational CRM built on TypeScript and PostgreSQL with a standardized People-Companies-Opportunities object model, REST and GraphQL API access at 100–200 requests per minute, and custom object support via its Metadata API. We map Spark contacts to Twenty's People object (resolving the company link via companyId), Spark companies to Twenty's Companies object, and Spark deals to Twenty's Opportunities object with stage value mapping. Spark's owner field resolves to Twenty's WorkspaceMember records by email match. Spark custom fields migrate as custom fields in Twenty, created via the Metadata API before data lands. Spark notes become Twenty notes with original timestamps. Spark tasks migrate as Twenty tasks linked to their parent records. Workflows, email sequences, and automation logic do not transfer — we export the definitions as a rebuild reference for Twenty's workflow builder. The migration runs via Twenty's REST API with batch processing to stay within rate limits, followed by a delta pickup window to capture any in-flight changes during cutover. File attachments in Spark require separate handling since CSV exports do not include binary files.
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 Spark CRM object lands in Twenty CRM, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
Spark CRM
Contact
Twenty CRM
People
1:1Spark contacts map 1:1 to Twenty's People object. The contact's name, email, phone, job title, and custom properties migrate directly. The company association requires a companyId lookup — Spark contacts without a linked company land in Twenty with no companyId and can be linked manually or via a post-migration script.
Spark CRM
Company
Twenty CRM
Companies
1:1Spark companies map to Twenty's Companies object. Company name, domain/website, industry, employee count, and annual revenue migrate directly. Spark company hierarchies (parent/child) map to Twenty's Parent CompanyId field if present. Multi-company associations on a single contact collapse to one primary companyId in Twenty — the most recently modified or primary-flagged company becomes the linked record.
Spark CRM
Deal
Twenty CRM
Opportunities
1:1Spark deals map to Twenty's Opportunities object. Deal name becomes the Opportunity name, deal amount maps to amount, and close date maps to closeDate. Spark deal stage names require value mapping to Twenty's opportunity stage pick-list — we capture the mapping in the migration plan before data lands. Deals without a linked company or contact attach to the Opportunity record without a foreign key; post-migration linking is available.
Spark CRM
Note
Twenty CRM
Note
1:1Spark notes migrate as Twenty notes. The note body maps to the Body field, and original create/update timestamps are preserved as custom datetime fields (CreatedAt__c and UpdatedAt__c) since Twenty's native timestamp reflects migration time. Notes linked to contacts or companies retain their parent record association via the Note's relationId field.
Spark CRM
Task
Twenty CRM
Task
1:1Spark tasks migrate as Twenty tasks. Task title becomes the Subject field, due date maps to dueDate, and completion status maps to status (completed/incomplete). Assigned owner resolves to a Twenty WorkspaceMember by email match. Tasks linked to contacts, companies, or deals carry their relationId forward so the task appears on the correct record in Twenty.
Spark CRM
Owner
Twenty CRM
WorkspaceMember
1:1Spark's owner field (user/rep assigned to a contact, company, or deal) resolves to Twenty WorkspaceMembers by email address. Unmatched owners are flagged before migration — your team either creates the Twenty user first or assigns records to a default owner. This step runs before any data migration so every record lands with a valid owner reference.
Spark CRM
Custom Field (on Contact)
Twenty CRM
Custom Field (on People)
1:1Spark custom fields on contacts require Twenty custom field creation via the Metadata API before migration begins. We create the field in Twenty matching the Spark field type (text, number, date, picklist) and then migrate values row-by-row. Picklist fields in Spark require value-by-value mapping to Twenty's select field options — we document this mapping in the pre-migration plan.
Spark CRM
Custom Field (on Deal)
Twenty CRM
Custom Field (on Opportunity)
1:1Spark custom fields on deals migrate as Twenty custom fields on Opportunities. The same Metadata API field creation process applies. For numeric custom fields (deal score, probability override), we preserve the raw value as a Twenty number field. Date custom fields map to Twenty date fields with original dates intact.
Spark CRM
Tag
Twenty CRM
Custom Multi-Select Field
1:1Spark's tag field (contact tags, company tags) requires transformation into Twenty's multi-select field type. We create a custom multi-select field called Tags__c on the People or Companies object and populate it with Spark's comma-separated tag values. If Spark has multiple tag fields, each becomes a separate multi-select field in Twenty.
Spark CRM
Attachment/File
Twenty CRM
Manual Re-Upload Required
1:1Spark file attachments are not included in CSV exports and cannot be migrated programmatically via Twenty's current import API. We document the attachment list (record + filename) in a reference CSV so your team can manually re-upload files to the correct Twenty records, or use Twenty's API to upload files post-migration if the attachment volume is manageable.
Spark CRM
Pipeline / Deal Stage
Twenty CRM
Opportunity Stage
1:1Spark deal stages map to Twenty's opportunity stage pick-list via value-by-value mapping. We capture every unique Spark stage name, map it to a Twenty stage with matching semantics (e.g., 'Closed Won' → 'Won'), and apply the mapping during the Opportunity migration. Stage order and probability mapping are documented for your Twenty admin to configure post-migration.
Spark CRM
Activity History (calls, emails, meetings)
Twenty CRM
Tasks and Notes
1:1Spark's activity history (logged calls, emails, meetings) migrates as a combination of Twenty tasks and notes. Call logs become tasks with Type='Call' and the call outcome in the task body. Email subjects become task subjects. Meeting records become tasks with a note attachment containing meeting details. Original activity timestamps are preserved in custom datetime fields.
| Spark CRM | Twenty CRM | Compatibility | |
|---|---|---|---|
| Contact | People1:1 | Fully supported | |
| Company | Companies1:1 | Fully supported | |
| Deal | Opportunities1:1 | Fully supported | |
| Note | Note1:1 | Fully supported | |
| Task | Task1:1 | Fully supported | |
| Owner | WorkspaceMember1:1 | Fully supported | |
| Custom Field (on Contact) | Custom Field (on People)1:1 | Fully supported | |
| Custom Field (on Deal) | Custom Field (on Opportunity)1:1 | Fully supported | |
| Tag | Custom Multi-Select Field1:1 | Fully supported | |
| Attachment/File | Manual Re-Upload Required1:1 | Fully supported | |
| Pipeline / Deal Stage | Opportunity Stage1:1 | Fully supported | |
| Activity History (calls, emails, meetings) | Tasks and Notes1:1 | 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.
Spark CRM gotchas
Multiple unrelated 'Spark CRM' products exist
Platform fee on top of monthly subscription affects long-term TCO
Payment-orchestration data is tightly coupled to Spark's runtime
Limited public review footprint for due diligence
Twenty CRM gotchas
Import order is enforced and critical
Export limited to 20,000 records and visible columns only
Soft-deleted records count toward uniqueness and trigger restores
API rate limits cap at 200 req/min on Organization tier
No native email sequences — follow-up cadences require external tools
Pair-specific challenges
Migration approach
Audit Spark data and map to Twenty schema
FlitStack AI connects to Spark via scoped read access to enumerate all contacts, companies, deals, activities, custom fields, and tags. We generate a data inventory report: record counts per object, custom field names and types, unique deal stage values, unique owner email addresses, and attachment counts. We then map every Spark object and field to its Twenty equivalent using the mapping tables above and flag any objects that cannot migrate automatically (attachments, workflows). This audit output becomes the migration plan reviewed by your team before any data moves.
Create Twenty schema for custom fields and custom objects
Before data can land, FlitStack AI creates the custom fields and custom objects in Twenty via the Metadata API. This includes custom fields for Spark properties that have no direct Twenty equivalent (tags as multi-select, original timestamps as datetime fields, source system IDs for traceability). We also create any custom objects in Twenty that mirror Spark custom objects, using the relationship model Twenty supports (one-to-many via foreign key, many-to-many via junction object). This step runs first so that the field definitions exist when data validation begins.
Resolve Spark owners to Twenty WorkspaceMembers by email
FlitStack AI extracts every unique owner email address from Spark contacts, companies, and deals and matches them against existing Twenty WorkspaceMember records by email. Unmatched owners are flagged with a list of Spark records assigned to them. Your team either creates the missing Twenty users before migration or designates a fallback owner. No record migrates without a valid Twenty WorkspaceMember reference — this prevents orphaned records that show no owner in Twenty's UI.
Migrate Companies, then People, then Opportunities in correct load order
FlitStack AI sequences the migration respecting Twenty's foreign-key constraints: Companies (the 'one' side of the relationship) migrate first via Twenty's REST API or CSV import. People records migrate second, resolving companyId lookups against the now-populated Companies table. Opportunities migrate third, resolving companyId and personId lookups against both Companies and People. Each batch processes in groups of 50–100 records with exponential backoff to stay within Twenty's API rate limits. Original create dates, update timestamps, and source system IDs are written to custom fields so Twenty's native audit trail reflects migration time rather than source-system time.
Run sample migration with field-level diff before full commit
A representative slice of 100–500 records — spanning contacts, companies, deals, and activities across multiple owners — migrates first into a staging area or a test Twenty workspace. FlitStack AI generates a field-level diff comparing source Spark values against the migrated Twenty values, so you can verify that email addresses, company links, deal amounts, stage values, and custom field values landed correctly before the full run commits. Any mapping errors are corrected in the migration plan, and the sample is re-run until the diff passes your team's validation criteria.
Execute full migration with delta pickup window for in-flight changes
The full migration runs against Twenty with a delta pickup window (typically 24–48 hours) that captures any records created or modified in Spark during the cutover window. Your team continues working in Spark during the migration — FlitStack AI uses scoped read access and does not modify Spark data. An audit log records every operation (records created, updated, skipped, or errored) with row counts and error details. One-click rollback is available if reconciliation fails. Post-migration, we deliver a summary report showing record counts, attachment reference list, and workflow export bundle for your Twenty admin.
Platform deep dives
Spark CRM
Source
Strengths
Weaknesses
Twenty CRM
Destination
Strengths
Weaknesses
Complexity grading
Standard CRM migration. 2 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 Spark CRM and Twenty CRM.
Object compatibility
2 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
Spark CRM: Not publicly documented on sparkcrm.io.
Data volume sensitivity
Spark CRM 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
Pick a category, then your source and destination platforms.
Category
FAQ
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