FormulaHub ETL

FormulaHub · The Product Lab · Design Partner

Build Better Data Integrations. Faster.

AI-native data integration powered by FormulaETL. Build with FormulaETL — or have FormulaHub implement it for you.

Bring Us Your Integration Explore FormulaETL

OSS on GitHub·Studio surface at formulahub.io/etl

Example pipeline

File in → warehouse out — inspectable end to end

Illustrative flow

SFTP
PGP
CSV
Validate
Formula Map
Dedupe
Snowflake
Archive

The problem

Legacy ETL is expensive, slow, and hard to maintain.

File drops, SFTP, PGP, schema drift, and fragile mappings still eat calendars and budgets. Tools that promised transformation often leave you with black boxes, brittle jobs, and a team afraid to touch production.

License and consulting stacks that outpace the value of the pipelines
Schema drift that breaks overnight jobs with no clear owner
SFTP + PGP + CSV hops glued together with tribal knowledge
Mappings nobody can inspect when finance asks why a row moved

What we do

Design through support — one Lab, one stack.

FormulaHub implements with FormulaETL, or you build on the OSS core yourself. Same product language either way.

Design

Map sources, transforms, and targets on a visual canvas your engineers can inspect.

Build

Ship pipelines with Field Mapper, validation, and Python where the logic needs it.

Migrate

Move fragile legacy jobs onto FormulaETL without a big-bang rewrite.

Validate

Prove row counts, schemas, and business rules before anything hits production.

Deploy

Run in your VPC, cloud, or ours — your data residency rules stay yours.

Support

Stay with the Lab after go-live: observability, drift, and the next integration.

Real product chrome — canvas, Field Mapper, Python runner.

Not fake SaaS fluff. FormulaETL is an open-source visual ETL studio: design on a canvas, map fields once, run Python in the flow, and self-host in the client VPC when that is the requirement.

Canvas

Visual ETL studio

Source → Field Mapper → Sink

Open source

Postgres · orders

Source

Field Mapper

Python · transform.py

Runner

Warehouse · facts

Sink

Drag nodes on the canvas, map fields once, run Python in the pipeline — ship the flow.

Open studioSelf-host in VPC

Field Mapper

Source → target fields

Map once. Reuse across runs.

order_id

→

fact_order_id

Mapped

customer_email

→

dim_email

Mapped

amount_cents

→

amount_usd

Cast

created_at

→

event_ts

Mapped

Python runner

transform.py · client VPC

Ready

def transform(row):
return normalize(row)

CanvasField MapperPython runnerClient VPC

Studio

Visual

Canvas + nodes

Mapper

Fields

Source to target

Deploy

VPC

Self-host with you

Illustrative product UI from the FormulaHub tile — same framing as the studio surface at formulahub.io/etl. Not a live iframe of your environment.

Example pipeline

SFTP → PGP → CSV → Validate → Formula Map → Dedupe → Snowflake → Archive

A familiar enterprise path: encrypted files land, get decrypted, parsed, validated, mapped, deduped, loaded, and archived — each hop visible on the canvas instead of buried in a job scheduler.

Step 01

SFTP

Step 02

PGP

Step 03

CSV

Step 04

Validate

Step 05

Formula Map

Step 06

Dedupe

Step 07

Snowflake

Step 08

AI proposes. FormulaETL proves.

Assistance without surrendering the pipeline. Visual where it helps, code where it must, open where it matters.

AI-assisted

AI proposes mappings, checks, and fixes. You stay in control of what ships.

Visual & inspectable

Canvas + Field Mapper — every hop is readable, not a black-box job.

OSS core

Open-source FormulaETL you can self-host. No lock-in theater.

Run anywhere

Client VPC, your cloud, or FormulaETL Cloud when you want managed ops.

Data quality

Validate, cast, and reject bad rows before they poison the warehouse.

Observability

Runs you can audit — lineage-friendly steps, not mystery batch scripts.

Warehouse-aware

Built with Snowflake and Databricks realities in mind — costs stay on your bill.

AI proposes / FormulaETL proves

Suggestions are proposals. Proof is in mapped fields, tests, and successful runs.

How engagement works

Six steps to production.

01
Bring the integration
Sources, sinks, SLAs, and the failure modes that keep your team up at night.
02
Scope with Engineering
We lock a Design Partner V1: one hard path to production, not endless tickets.
03
Design on FormulaETL
Canvas, Field Mapper, and validation rules your team can review in the open.
04
Build & migrate
Replace fragile scripts and expensive legacy hops with inspectable pipelines.
05
Prove with your data
DQ checks, sample runs, and sign-off before cutover — AI proposes, FormulaETL proves.
06
Deploy & support
Production in your environment or Cloud, with Lab support after go-live.

Design Partner

Bring us your hardest data integration.

Design Partner work for teams with real production pressure: one painful path, clear standards, and a Lab that ships. Build with FormulaETL or have FormulaHub implement it for you.

Bring Us Your Integration

Pricing

Clear lanes. No checkout theater.

FormulaETL pricing is separate from FormulaHub consumer products. Your Snowflake, Databricks, and AWS costs stay on your accounts — we do not resell your cloud bill.

Community

Self-host the OSS core. Build and run FormulaETL yourself.

Get FormulaETL on GitHub

FormulaETL Cloud

From $1,500/mo

Managed FormulaETL Cloud, starting at $1,500/mo. Talk to Engineering to size it.

Talk to Engineering

Implementation & Migration

Custom

FormulaHub designs, builds, migrates, and validates with you. Pricing fits the integration — Talk to Engineering.

Talk to Engineering

No Stripe checkout on this page for FormulaETL. Cloud and implementation start with a conversation with Engineering — not a self-serve buy button.

FormulaHub ETL

Talk to Engineering.

Ready for a Design Partner engagement? Tell us the integration that hurts most. We will reply from the Lab.

Talk to Engineering Explore FormulaETL

support@formulahub.ai · subject prefilled for Design Partner