Parabola
Drag-and-drop data workflows for spreadsheets, APIs, ecommerce, and operations
The visible visual data automation loop is buildable, but a credible replacement needs more than the first screen. Parabola earns its keep through connectors, auth, reliability, so expect a weekend or multi-day build and a narrower personal scope.
Build verification: not recorded. How we judge buildability
What you give up
- durable execution at scale
- schema drift handling and enterprise controls
- hundreds of maintained connectors
- OAuth app verification
Why people still pay
Parabola: One automation is easy. Subscribers pay for maintained integrations, credentials, retries, observability, and someone else owning breakage.
Your build guide
The stack, security requirements, and agent rules for a focused replacement.
Before you start
- Runtime and tools: TypeScript, Node, PostgreSQL and a database-backed job worker with a small React run inspector.
- Before starting: Credentials for only the chosen integrations, their current API documentation, example payloads and an always-on worker for schedules.
Use these project rules and optional skill references alongside the prompt. Review each skill before adding it to your agent; the AGENTS.md export includes the same guidance.
Project rule — domain: Store DatasetVersion, TransformNode, JoinKey, RowError and OutputSnapshot; joins declare one-to-one or one-to-many cardinality and retain source-row lineage.
Project rule — scope and recovery: Start with import/filter/map/join/export only. Preview row counts at each step, cap memory and use explicit approval before overwriting any destination.
Project rule — acceptance: Join an order to two duplicate SKU cost rows; flag the ambiguous join rather than doubling revenue, and show source rows responsible for the error.
Project rule — delivery: document real setup commands and permissions; do not claim a build, accuracy level, performance result or security certification that has not been demonstrated.
Recommended skill: supabase-postgres-best-practices — review this PostgreSQL domain schema, uniqueness constraints, transaction boundaries and access-scoped queries; Supabase hosting is not required. Follow the maintainer's installation instructions and match its requirements to the chosen runtime.
Recommended skill: sharp-edges — review configuration and API defaults against the app-specific invariants and recovery boundaries above; this is not a security certification. Follow the maintainer's installation instructions and match its requirements to the chosen runtime.
Implementation plan
Phase 1
Pin the working slice and create its example input: Import orders from CSV, join a product-cost lookup, flag invalid rows and export a reconciled operations table with a visible transformation graph. Confirm setup: Credentials for only the chosen integrations, their current API documentation, example payloads and an always-on worker for schedules.
Phase 2
Implement persistence and write-time invariants before decorating the UI: Store DatasetVersion, TransformNode, JoinKey, RowError and OutputSnapshot; joins declare one-to-one or one-to-many cardinality and retain source-row lineage.
Phase 3
Connect the working view to real saved state. Persist trigger identity, step input version and external receipts before marking success. Retry bounded transient failures; unknown write outcomes require reconciliation. Do not promise exactly-once execution across external services.
Phase 4
Expose the app-specific limits and recovery path in context: Start with import/filter/map/join/export only. Preview row counts at each step, cap memory and use explicit approval before overwriting any destination.
Phase 5
Walk through this concrete acceptance case and preserve its exported evidence: Join an order to two duplicate SKU cost rows; flag the ambiguous join rather than doubling revenue, and show source rows responsible for the error. Finish the README and backup/restore instructions; report unfinished capabilities explicitly.
Build the following focused alternative to Parabola. This is a deliberately limited personal or small-team substitute, not parity with the paid service. WORKING SLICE Import orders from CSV, join a product-cost lookup, flag invalid rows and export a reconciled operations table with a visible transformation graph. SETUP AND ARCHITECTURE Use TypeScript, Node, PostgreSQL and a database-backed job worker with a small React run inspector. Prerequisites: Credentials for only the chosen integrations, their current API documentation, example payloads and an always-on worker for schedules. Before integrating anything, record actual versions and permissions, plus model files or provider limits only where used, in the README; make unavailable dependencies visible rather than simulating success. DOMAIN MODEL AND INVARIANTS Store DatasetVersion, TransformNode, JoinKey, RowError and OutputSnapshot; joins declare one-to-one or one-to-many cardinality and retain source-row lineage. IMPLEMENTATION CONTRACT Persist trigger identity, step input version and external receipts before marking success. Retry bounded transient failures; unknown write outcomes require reconciliation. Do not promise exactly-once execution across external services. Provide an input/setup view, the main work view, and a review/export view appropriate to this workflow. Preserve the last saved state if a job or save fails. Include empty, loading, permission-denied, partial and retryable-error states. Log identifiers and error categories without secret values or unnecessary private content. APP-SPECIFIC BOUNDARY AND RECOVERY Start with import/filter/map/join/export only. Preview row counts at each step, cap memory and use explicit approval before overwriting any destination. ACCEPTANCE SCENARIO Join an order to two duplicate SKU cost rows; flag the ambiguous join rather than doubling revenue, and show source rows responsible for the error. Also reopen the app after an interrupted operation, confirm the saved record/export remains inspectable, and document the recovery action. These are implementation acceptance requirements, not a claim that this guide has been tested. DELIVERY Deliver a runnable repository with migrations or project-format versioning, a non-sensitive example, environment/permission setup, the exact manual acceptance steps, and a backup/export-and-restore walkthrough. Implement the working slice before optional integrations; list any deferred paid-product capabilities honestly. Do not add capabilities outside the working slice just to resemble the original product. PROJECT RULES FOR AGENTS.md Keep the domain invariants above executable at the write boundary. Propose scope changes before adding providers or permissions. Never fabricate source evidence, publish results, identity matches or successful delivery. Preserve user originals and require an explicit confirmation for destructive changes or external publication.
$ open in your agent (prompt prefilled, you press enter), copy the prompt or copy or download AGENTS.md · generated from this app's build plan
prompt copied. want to know what dies next week?
new verdicts + top votes, weekly. free. one-click out.
Alternatives to building your own
no votes, no pay-to-list · just what's real
Parabola pricing
| plan | monthly | annual (per mo) | what you get |
|---|---|---|---|
| basic | $0/workspace | $0/workspace | 1 user; 1,000 credits/month; unlimited flows; limited AI usage; hard stop at the monthly cap. |
| explorer | $20/workspace | — | 1 user; 1,500 credits/month; 250 MB table storage; daily scheduling.Additional usage is $0.18 per 10 credits. |
| collaborator | $400/workspace | — | Up to 3 users; 30,000 credits/month; custom scheduling.Self-service monthly plan. |
| business | — | — | Unlimited users; custom credit allotment, storage, scheduling and security.Custom contract; annual credit allotments may apply. |
free tier1 user, 1,000 credits/month, unlimited flows and a hard stop at the cap
billingself-service plans are monthly only; Business is custom and may be annual
hidden costsExplorer charges $0.18 per additional 10 credits. Credits are charged on flow runs; paid plans move into pay-per-credit usage, while failed or zero-row steps may not count. Cancellation can immediately finalize accrued overage.
pricing sources checked 2026-08-11 · pricing source ↗
Questions about Parabola
Can you build your own Parabola with AI?
Partly. The visible visual data automation loop is buildable, but a credible replacement needs more than the first screen. Parabola earns its keep through connectors, auth, reliability, so expect a weekend or multi-day build and a narrower personal scope.
What does the Parabola build prompt cover?
The prompt starts with this scope: Import orders from CSV, join a product-cost lookup, flag invalid rows and export a reconciled operations table with a visible transformation graph. Full-product capabilities excluded from the comparison include: durable execution at scale; schema drift handling and enterprise controls; hundreds of maintained connectors. Follow the implementation plan and its prerequisites before expanding the build.
How do I use the prompt, AGENTS.md and agent skills?
Start with the Parabola prerequisites and stack, then copy the prompt into your coding agent. Save the project rules as AGENTS.md in the project root. Linked skills are optional packages or source instructions for specific tasks; review their current contents and install only those matching the chosen stack. A skill does not supply API credentials or verify the finished app.
How long will this Parabola project take?
The catalogue estimate is weekend to multi-day for the limited scope. Setup, integration approvals, debugging, deployment and ongoing maintenance can add time. This is an estimate, not a delivery guarantee.
What would I give up by replacing Parabola?
durable execution at scale; schema drift handling and enterprise controls; hundreds of maintained connectors; OAuth app verification. Parabola: One automation is easy. Subscribers pay for maintained integrations, credentials, retries, observability, and someone else owning breakage.
What can I use instead of building Parabola?
KNIME Analytics Platform: A visual data workbench with hundreds of connectors; scheduled cloud runs are where KNIME starts charging. Check each option's license, hosting needs and feature limits.