High-speed bulk data movement

Move the full dataset.
In record time.

Omni Loader moves very large datasets across databases, cloud warehouses, and data lakes with parallel workers, adaptive tuning, and durable recovery.

Plan a bulk migration Explore the platform
Broad paths

Move between operational databases, warehouses, lakes, and files.

Adaptive loading

Use provider bulk APIs, multi-row SQL, direct writers, or native ingestion by target.

Resumable work

Retry unfinished tables and slices without restarting completed migration work.

Full verification

Compare counts, table hashes, or records before the target is ready for cutover.

Built for the full load

Parallel by default. Recoverable by design.

Move tables, files, and large binary values without turning every migration into a custom engineering project.

Massive parallelism

Auto-slice large tables and move many objects concurrently without hand-built partition plans.

Explore capability →

Resume and recover

Restart unfinished work units instead of restarting a multi-terabyte migration.

Explore capability →

Self-tuning

Start with production-minded defaults, then override the exceptional tables precisely.

Explore capability →

Warehouses and lakes

Prepare analytics-ready files and hydrate cloud destinations at the speed they ingest.

Explore capability →

Schema conversion

Plan target schemas, types, tables, indexes, sequences, counters, and foreign keys.

Explore capability →

Adaptive loading

Choose provider bulk APIs, multi-row SQL, direct writers, or native ingestion by target.

Explore capability →

Validation

Verify completed loads with counts, table hashes, or record-level comparison.

Explore capability →

Snapshot reconciliation

Persist added, changed, and deleted differences and optionally repair the target batch.

Explore capability →

Parallel movement

Turn a large catalog into independent work.

Omni Loader discovers the shape of the source, splits the work where it helps, and keeps tables and slices moving concurrently. The result is a migration that exposes progress instead of hiding it behind one oversized job.

Many tables at once

Independent work units let small tables finish while the largest tables continue to be sliced.

One durable run

Checkpoints preserve completed work so recovery stays targeted when a slice or destination needs attention.

Multiple Omni Loader agents coordinating parallel migration work

Heterogeneous estates

From source to destination, one visible path.

From operational databases to warehouses, lakes, and files, Omni Loader keeps source selection, target preparation, parallel movement, and verification in the same migration plan.

Omni Loader connecting multiple database sources and targets

One movement engine

Start with the path. Keep the workflow in one place.

Omni Loader is built for the work around the copy itself: understanding the source, preparing the target, selecting the right loading route, and proving that the result is ready to use.

Operational migrations

Database to database

Move tables between heterogeneous engines while mapping schemas, types, indexes, sequences, counters, and foreign keys as part of the same project.

Review supported databases

Analytics delivery

Database to lake or warehouse

Turn row-oriented source data into target-ready files, stage them in cloud or local storage, and let the destination ingest in parallel.

Explore staged ingestion

Reshaping at scale

Consolidation and extraction

Combine aliased source catalogs into one target, filter what moves, or externalize large binary values to object storage during the migration pass.

See migration patterns
Omni Loader deployment topology connecting source, agent, and destination systems

Deploy where the work lives

Keep the control plane light. Put movement near the data.

Run agents close to the source and destination, use local credentials and network paths, and keep the row movement on infrastructure you control. Omni Loader coordinates the plan without turning the control plane into a data bottleneck.

See deployment options

A runbook your team can use

From source inventory to cutover evidence.

Large migrations become easier to operate when each decision has a place in the run. Omni Loader keeps discovery, configuration, movement, recovery, and validation connected instead of leaving the critical details in separate scripts and spreadsheets.

The result is not just a copied database.

It is a reviewed target, a recorded execution path, and a validation result the migration team can use to make the cutover decision.

Discover

Inspect metadata, table sizes, keys, partitions, object dependencies, and the limits of both ends of the path.

Shape

Select tables and columns, map names and types, choose creation policy, define filters, and scope exceptions to the tables that need them.

Move

Run independent tables and bounded slices concurrently, using the writer and staging strategy that fits each target.

Prove

Review counts, table hashes, or record-level comparisons, inspect differences, and decide when the target is ready for cutover.

Validation that stays visible

Finish with evidence, not a hunch.

Counts tell you whether the shape matches. Hashes and record-level comparison tell you where it does not. Omni Loader turns differences into a reviewable result and lets the team decide what to repair before cutover.

The target is ready when the evidence says it is.

Keep the run history, comparison scope, and exceptions together with the migration plan.

Omni Loader validation and reconciliation paths expanding from a completed migration

Operational control

Meet the migration window. Respect production limits.

The best migration speed is the speed your infrastructure can sustain. Start with practical defaults, measure the full path, and make the exceptional choices visible to the operator.

Bound the pressure

Set worker concurrency, bandwidth, batches, buffers, and ingestion capacity around the source, network, and target limits you need to respect.

Keep progress visible

Follow status at the run, stage, table, and slice level. Completed work stays accounted for while supported failed tasks can be cleaned up and replayed.

Automate the repeatable parts

Save the migration plan, run it from the console or scheduler, keep configuration in source control, and retain the evidence needed for review.

Adapt to the destination

Use the writer that fits the target.

Bulk APIs, multi-row SQL, direct writers, and native ingestion are implementation details the platform can choose per destination. You get a measured path with clear controls for workers, batches, buffers, and pressure.

Omni Loader adaptive loading paths represented as connected target-aware components

One executable migration plan

Discover, shape, move, and prove the target.

Discover

Read source and target metadata, sizes, partitions, and object dependencies.

Shape

Select data, map names and types, preview DDL, and set table overrides.

Move

Slice work, choose adaptive writers, and stage cloud ingestion in parallel.

Prove

Create dependent objects, validate results, and review run history and differences.

Move the full dataset without babysitting the job.

Tell us the source, destination, data volume, and migration window.

Plan a bulk migration Explore supported databases