Full-stack automation (design → deploy)
Generate technical specs and project plans up front; auto-provision IAM roles, Glue triggers, jobs, and S3 layouts—no brittle manual scripts.
Zero-downtime snapshot + sync
Migrate historical data and continuously capture live changes with idempotent, resumable jobs for clean, repeatable cutovers.
Integrity by default
Built-in reconciliation (schema + data), precision/scale checks, and automated rollbacks protect production and ensure 1:1 fidelity.
Performance & cost optimization
Intelligent micro-batching and Iceberg compaction reduce tiny files, keep metadata lean, and sustain query performance at scale.
Full-stack automation (design → deploy)
Generate technical specs and project plans up front; auto-provision IAM roles, Glue triggers, jobs, and S3 layouts—no brittle manual scripts.
Zero-downtime snapshot + sync
Migrate historical data and continuously capture live changes with idempotent, resumable jobs for clean, repeatable cutovers.
Integrity by default
Generate technical specs and project plans up front; auto-provision IAM roles, Glue triggers, jobs, and S3 layouts—no brittle manual scripts.
Performance & cost optimization
Generate technical specs and project plans up front; auto-provision IAM roles, Glue triggers, jobs, and S3 layouts—no brittle manual scripts.
The 4 Models of The Solution
Assessment & Planning Model
Maps your current Delta Lake estate and generates a migration blueprint before any code runs. What it does: dependency graphing, table criticality scoring, target Iceberg spec, S3/Glue/IAM plan, runbooks and timelines. Outcomes: complete technical spec + project plan; predictable scope and effort.
Bulk Snapshot & Historical Migration Model
Moves large data estates quickly and safely. What it does: parallelized snapshot copy, schema evolution on-the-fly, precision/scale preservation, Iceberg table creation, and automatic layout/partitioning. Outcomes: validated historical baseline in S3 Tables, ready for incremental sync.
Incremental Change Capture & Cutover Model
Keeps target in lockstep with live source until switch-over. What it does: robust watermarking/state management (leveraging Delta CDF where available), MERGE correctness, idempotent/resumable jobs, blue/green cutover, and “last-known-good” rollbacks. Outcomes: zero-downtime migration with clean
re-runs and safe fallbacks.
Validation, Governance & Optimization Model
Guarantees integrity and sustained performance post-migration. What it does: deep schema & data reconciliation (beyond row counts), timestamp/number fidelity checks, compaction scheduling, small-file mitigation, alerts on drift, and policy gates before every run. Outcomes: trusted data, predictable SLAs, and lower ongoing costs.
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