ClickHouseCalc Audit: Self-Hosted MergeTree vs Google BigQuery On-Demand ($6.25/TB Scan)
In our deterministic ClickHouseCalc model, Google BigQuery On-Demand excels for infrequent ad-hoc warehouse joins over petabyte lakes, whereas high-concurrency customer dashboards or 30-second Grafana refreshes trigger recurring $6.25/TB scan charges that fixed-cost ClickHouse NVMe nodes avoid.
ClickHouseCalc Tariff & Storage Architecture Matrix (clickhouse-vps-vs-bigquery-on-demand)
| OLAP Audit Dimension | Incumbent Platform | Self-Hosted ClickHouse MergeTree |
|---|---|---|
| Published Per-Query Scan Tariff (Retrieved 2026-11-12) | $6.25 per TB scanned (after 1 TB monthly free tier) | $0.00 per query — unlimited BI & Grafana refreshes |
| Streaming Write API Ingestion Rate | Published per-GB Storage Write API tariff above free quota | $0.00 — native `async_insert` or Vector HTTP sink |
| Query Execution Storage Architecture | Stateless distributed slot spin-up over Colossus storage | Local PCIe Gen4 NVMe + pinned RAM `primary.idx` marks (verify p95 query latency on target NVMe) |
| Modeled Monthly Bill (50 BI Viewers · 80 TB Raw Dataset) | ~$1,850–$4,600/mo depending on refresh frequency | $19.99–$79.00/mo fixed server tariff (verify at checkout) |
ClickHouseCalc Architectural Deep Dive: clickhouse-vps-vs-bigquery-on-demand
Why ClickHouseCalc Separates Ad-Hoc Data Lakes From High-Refresh BI Serving
Even when BigQuery tables are partitioned by date and clustered by tenant ID, a multi-tile Metabase or Superset dashboard refreshing across 90 days scans substantial column bytes multiplied by every active user session. Keeping BigQuery for cold ELT joins while serving live customer analytics from a ClickHouse MergeTree replica eliminates per-scan billing anxiety.
ClickHouseCalc Incremental Materialized Views for Embedded SaaS Dashboards
By pre-aggregating daily and hourly cohorts into `AggregatingMergeTree` target tables on an AMD EPYC KVM VPS or UltaHost NVMe VDS, SaaS products can expose live tenant analytics without metering individual SQL queries.