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Use case

Real-time lakehouse

TwinCommit keeps your lakehouse seconds behind production by streaming committed transactions from operational databases straight into Delta, Hive, Iceberg or Snowflake tables, with deletes and ordering preserved.

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Outcomes

✓Fresh data for BI, ML and AI in seconds

✓No nightly batch extracts against production

✓Deletes and updates applied correctly, not appended

How it works

Real-time lakehouse with TwinCommit

  1. 1

    Capture

    Read changes from the source log with zero source-side objects.

  2. 2

    Stage

    Write micro-batches as Parquet or ORC to cloud storage.

  3. 3

    Merge

    Apply with MERGE semantics so the lake mirrors the source exactly.

Common routes for real-time lakehouse

→Db2 → Databricks→Oracle → Databricks→SQL Server → Synapse→Oracle → ADLS→Db2 → S3→SQL Server → Snowflake→MySQL → BigQuery→PostgreSQL → Redshift→SAP HANA → Snowflake→Oracle → Hive→MongoDB → Databricks

More use cases

Zero-downtime migrationMainframe offloadDisaster recoveryLegacy modernizationCache & search sync

Replicate your first table in five minutes.

Download the free Developer edition, or have one of our replication engineers walk you through a migration plan.

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