1.9 Worked examples
Analysts need to join across 3 of them. Data volume says "no warehouse needed" — but the silo argument says yes, because you cannot join across three separately-owned OLTP databas…
① Is my data big enough to need a warehouse? A company with 50 GB of operational data across 6 services. Analysts need to join across 3 of them. Data volume says "no warehouse needed" — but the silo argument says yes, because you cannot join across three separately-owned OLTP databases in one query. Reason #1 (silos) triggers long before reason #3 (query cost). This is the most common mis-diagnosis: teams wait for the data to get big, when the real trigger was organizational.
② The cost of an idle analytical cluster. A 20-node cluster provisioned for peak query load, used 3 hours a day. Utilization = 3/24 = 12.5%. You pay for 24 hours of 20 nodes and use 3. In the cloud, the same workload with elastic compute costs ~1/8 as much. This is precisely the "analytical systems have extremely variable load" argument for cloud — and the counter-case is a predictable load, where owning hardware wins.
③ Object store vs virtual disk, per I/O. A query reading 10,000 blocks.
- Local NVMe: ~100 µs/block → 1 second
- Virtual block device (EBS): every I/O is a network call, ~500 µs → 5 seconds, and highly sensitive to network jitter
- Object store, 10,000 separate GETs: ~20 ms each → 200 seconds ✗
- Object store, 40 batched range reads of 250 blocks: ~50 ms each → 2 seconds ✔ This is why cloud databases "pack many small values into large blocks before writing to the object store." The access pattern matters more than the storage tier.
④ Tail latency across services (a preview of Ch 2). A request fans out to 30 microservices, each with p99 = 50 ms. P(no service is slow) = 0.99³⁰ ≈ 74% → 26% of user requests hit at least one p99-slow call. Distribution didn't just add latency; it converted a 1-in-100 event into a 1-in-4 event.
⑤ Data minimization as a cost calculation. You're deciding whether to retain precise location history for 2 years.
- Storage cost: trivial, maybe $200/month
- Breach liability: location data revealing clinic visits, places of worship, or union meetings — for every user
- Compliance exposure: GDPR requires a specified explicit purpose and no longer than necessary
- Compelled disclosure: a subpoena reaches whatever exists The storage bill is the smallest term in the equation, and it's usually the only one anyone computes.