HyperLake — Batch and real-time analytics without competing for one engine
FREE PLANNING CHECKLIST

Velocity Lakehouse combines open tables with a ClickHouse hot tier and separate transformation capacity. Plan how batch, interactive and existing warehouse work will be divided.

Prepare these inputs
[ ] Batch and interactive query examples
[ ] Freshness targets and data volumes
[ ] Existing warehouse dependencies

Your first workflow
[ ] Classify workloads by freshness, latency and retention.
[ ] Pilot one dataset through batch and hot-tier paths.
[ ] Validate routing, reconciliation and cost before consolidating systems.

Acceptance checks
[ ] Reconcile hot-tier and table results.
[ ] Check interactive latency while batch work runs.
[ ] Document replay and recovery for each tier.

Decision criteria
[ ] Which data belongs in the hot tier versus open tables?
[ ] What freshness and concurrency does each consumer need?
[ ] Which warehouse workloads should remain where they are?

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/batch-realtime-lakehouse

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