HyperLake — An open Iceberg lakehouse: plan tables, access and migration
FREE PLANNING CHECKLIST

Openhouse combines Iceberg, Trino and dbt on your own object storage. Make table ownership, interoperability and workload fit explicit before migrating an existing lake.

Prepare these inputs
[ ] Table inventory and storage layout
[ ] Transformation jobs and consumer engines
[ ] Access and data-quality requirements

Your first workflow
[ ] Select one dataset with known consumers and acceptance checks.
[ ] Build the table and transformation path alongside the current system.
[ ] Check interoperability and operations before retiring the old path.

Acceptance checks
[ ] Validate schema and data reconciliation.
[ ] Test reads from each required engine.
[ ] Review lifecycle, recovery and storage charges.

Decision criteria
[ ] Which engines must read the same tables?
[ ] Who owns schemas, compaction and data quality?
[ ] How will existing warehouse jobs coexist during transition?

Cost and scope
Compare the cloud bill, platform charges, operating effort and migration work for the same workload. Cloud capacity is not free. Charges and scope need agreement before paid deployment.

Before switching
AWS and Google Cloud are available today; other deployment environments are roadmap. Preserve the existing workload and access path until compatibility, recovery and cutover checks pass.

Sources
https://hyperlake.cloud/stacks
https://hyperlake.cloud/faq
https://hyperlake.cloud/get-started

Next step
No free cloud capacity is promised. Deployment scope and charges are agreed separately; AWS and Google Cloud are available today.
https://hyperlake.cloud/solutions/open-iceberg-lakehouse

This is a planning template, not a completed assessment or a quote. No personal data is required to download it.