data · open source
Data Warehouse Migration with Apache Kafka
Data Warehouse Migration built on Apache Kafka, chosen where it genuinely fits, and swapped where it does not.
- Category
- data
- Vendor
- Open source
- Alternatives we also use
- 6
Why Apache Kafka for this
SQL dialects differ in ways that quietly change results, especially around nulls, dates and rounding. We document every behavioural difference rather than assuming equivalence.
Apache Kafka is strongest at throughput and durable replay of event history. For data warehouse migration that matters because the failure modes of this kind of system tend to cluster exactly there.
The honest trade-off: significant operational complexity unless you are genuinely at streaming scale. We say that up front because a stack chosen for fashion rather than fit becomes someone's migration project two years later. Every engagement opens with a measurement: the cycle time, the cost per transaction, or the error rate we are being asked to move.
You own the code, the models where they are open-weight, and the documentation to run it without us.
The honest assessment
- What it is
- Distributed event streaming for high-throughput real-time pipelines.
- Strongest at
- throughput and durable replay of event history
- Trade-off
- significant operational complexity unless you are genuinely at streaming scale
- Category
- data
We are not a reseller for Apache Kafka and hold no commission on this choice. Where a different option fits your workload better, the recommendation will say so. That is the entire value of asking us.
What is included
- Inventory of every table, job and downstream consumer
- Query translation with behaviour differences documented
- Row-level and aggregate reconciliation between old and new
- Dual running until the numbers agree
- Staged cutover by consumer group
- Cost model comparing before and after
Questions
How do you avoid breaking reports?
Row-level and aggregate reconciliation between old and new, plus dual running until the numbers agree. Consumers move in stages, never all at once.
Which warehouse should we move to?
It depends on workload and existing cloud. We model cost against your real query patterns rather than list pricing, and sometimes the answer is to stay.
How long does it take?
Driven by the number of downstream consumers far more than data volume. The inventory in week one gives a realistic estimate.
Alternatives for data warehouse migration
Same capability, different stack. Each page states its own trade-off.
What else we build on Apache Kafka
Building with Apache Kafka?
Bring us the workload and we will tell you whether this is the right stack for it.
Or email bd@dtrasglobal.com · call +91 74118 77878