Product

Data Integration

ELT and ETL pipelines built through a guided wizard, scheduled and orchestrated for you, landing in your own warehouse—with no infrastructure to stand up and no copy of your data kept in ours.

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Move your data once, and keep it moving

The hard part of integration was never the first load—it's the next thousand. InfiniStack turns a source, a destination, and a schedule into a managed pipeline with its own compute, automatic retries, and a full run history you can audit.

Choose ELT to land raw data and shape it later in the warehouse, or ETL to reshape records in flight. Either way the data comes to rest in your own warehouse.

Connectors
MySQL & PostgreSQL
Modes
ELT and ETL
Execution
Dedicated per org
Data storage
Your warehouse only

Two ways to run a pipeline

The same builder, the same schedule, the same run history. The only question is where the shaping happens—after the load, or during it.

Default

ELT pipelines

Extract from the source, load it into your warehouse as-is, and transform it there—where the compute already lives and the raw record is still available to re-derive from.

  • Incremental sync — each run picks up where the last one stopped, using the replication key you choose, instead of re-reading the whole table.
  • Backfill when you need it — reset a pipeline's sync state to re-read the table from scratch.
  • Raw stays raw — the loaded table is the source of truth, so a modelling mistake costs you a re-run of a transformation, not a re-sync.
Opt in per pipeline

ETL pipelines

Turn transformations on in the builder and records are reshaped in flight—renamed, derived, masked, or dropped—before they ever reach the destination table.

  • Column-level rules — rename fields, drop what you don't need, and add derived fields from an expression.
  • Keep sensitive fields out — mask or exclude a column at the pipeline, so it never lands in the warehouse at all.
  • See it on real rows — the builder samples your source, so you can check a rule against actual data before saving.
  • Same pipeline either way — ETL is a toggle on the pipeline, not a different product to learn.

The pipeline builder, step by step

A guided wizard that ends in a working, scheduled pipeline—no YAML to hand-write, no runner to provision.

Step 1

Pick a source

Choose MySQL or PostgreSQL as your source and enter the connection details once. They're scoped to your organization alone, with access controlled by role.

MySQL PostgreSQL
Step 2

Select a table and replication key

InfiniStack discovers the tables the source exposes. Pick the table this pipeline will sync, choose the replication key it uses to track new and changed rows, and set a row limit. Each pipeline syncs one table, incrementally.

Schema discovery One table per pipeline Incremental sync
Step 3 — ETL only

Add in-flight transformations

If you turned ETL on, this is where you rename columns, mask sensitive fields, or derive a new one from an expression—checked against a sample of your real source rows before you move on. Leave ETL off and the wizard skips this step entirely.

Step 4

Choose a destination

Point the pipeline at your MySQL or PostgreSQL database and name the table it writes to. The destination is yours—InfiniStack orchestrates the load, it doesn't hold the result.

Step 5

Preview the result

Run a sample before you commit. You see the rows the pipeline would actually produce—after your column choices and any transformations—so mistakes get caught in the wizard rather than in production.

Step 6

Name it and set a schedule

Give the pipeline a name your team will recognise and pick how often it runs. From here on it's orchestrated for you—no cron entry to maintain, no worker to keep alive.

Step 7

Review and activate

One screen with every choice you made—source, streams, transformations, destination, schedule—before anything runs. Confirm, and the pipeline is live.

Scheduling and orchestration, handled

Once a pipeline is live, the part that usually becomes someone's second job—keeping it running—is the part we operate.

Configurable schedules

Set the cadence per pipeline—frequent syncs for the sources your team watches, nightly for the ones they don't.

Retries, then pause

A failed run doesn't stop the schedule—the next run tries again. After 5 failed runs in a row, the pipeline is paused and you're notified.

Full run history

Every run keeps its status, timing, row counts, and logs—so "when did this table last update?" has an answer.

Versioned changes

Edit a live pipeline as a draft, save it as a version, and activate when you're ready—the running one keeps running meanwhile.

Isolated compute, per organization

Your pipelines don't queue behind anyone else's. Each organization gets its own provisioned project and dedicated runners, so a large backfill elsewhere on the platform doesn't change how fast your nightly sync finishes. See Architecture for how the isolation is built.

What happens after the data lands

Connectors

Browse the sources and destinations a pipeline can be built on.

 Explore

Architecture

How per-tenant isolation, dedicated runners, and your-warehouse-only storage fit together.

 Explore

Common questions

Should I use ELT or ETL?

ELT is the default and the right answer most of the time—land the raw data, then model it in the warehouse where you can always re-derive. Reach for ETL when a field must never reach the destination at all, such as something you need masked or dropped before it lands.

Does every run re-read the whole table?

No. Pipelines replicate incrementally, picking up from where the previous run stopped. When you actually want the whole table again, reset the pipeline's sync state to backfill.

Where does the data end up?

In the destination you configured—your own warehouse or database. InfiniStack orchestrates the movement and keeps the run metadata, but your records are not copied into a separate analytics store we operate.

Can I change a pipeline that's already running?

Yes. Edits are made as a draft and saved as a version; the currently active version keeps running until you activate the new one, so a change in progress never takes a live sync down.

Which sources and destinations are supported?

Today, MySQL and PostgreSQL. More connectors are added to the library over time.

Who can see my source credentials?

Connection details are scoped to your organization alone. Access follows the same role-based model as the rest of the platform—see Security.

Build your first pipeline today

Connect a source, pick your streams, set a schedule—and watch it land in your own warehouse.

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