vendor lock-in → exit plan
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Data Warehouse migration path

From Google BigQuery to ClickHouse

Cost comparison, a phase-by-phase migration plan, and the automation to execute it.

Effort
Medium
Est. timeline
~15 wks
ClickHouse model
Free OSS / Cloud
Open source
Yes
▶ Model your savings in the calculator

3-year cost calculator

Pre-filled for Google BigQuery → ClickHouse. Adjust every figure with your own numbers.

Every figure here is an illustrative estimate, not a vendor quote. Defaults are editable starting points compiled from public information; real, binding pricing comes from the vendor or an authorized distributor. See our methodology.

Sized at 200 TB managed — cost is computed on this.
Stay on Google BigQuery (3yr)
$720,000
Move to ClickHouse (3yr + migration)
$180,000
Projected savings
$540,000 (75%)
Payback period
3.6 mo
Build a decision report from these numbers:

All figures are illustrative and fully editable — adjust the cost-per-TB and migration inputs with your own numbers. Not guaranteed vendor pricing (defaults reviewed May 2026). For a binding quote, use the request form below to reach an authorized distributor or partner.

Quick comparison: Google BigQuery vs ClickHouse

Common trade-offs teams weigh when staying on Google BigQuery versus moving to ClickHouse. These are general, commonly-reported considerations — not statements of fact about any vendor — so check them against your own contract and the vendors' current terms.

Google BigQuery Current
Google · Usage (per TB scanned)
  • Already in production — no migration effort or risk
  • Mature ecosystem with vendor support and SLAs
  • Per-TB-scanned billing penalizes wide queries
  • Costs spike with unoptimized queries
  • Storage + compute + egress stack up
  • Ongoing usage (per tb scanned) cost to budget for
ClickHouse Planned
Open source · Free OSS / Cloud
  • Open source — no license fees
  • No vendor lock-in
  • Cost model: Free OSS / Cloud
  • Requires a migration (~15 weeks, medium effort)
  • Community support by default — paid support optional

Why teams evaluate alternatives to Google BigQuery

Reasons commonly cited by users and in public industry coverage for re-evaluating Google BigQuery. These are general, reported considerations — not statements of fact about Google — and may not reflect your situation or the vendor's current terms. Verify against your own contract before deciding.

  • Per-TB-scanned billing penalizes wide queries
  • Costs spike with unoptimized queries
  • Storage + compute + egress stack up

The migration plan

Roughly 15 weeks for a mid-size estate, in six phases.

Assessment & discovery
Inventory every workload, dependency, and integration; flag anything high-risk.
Target design & sizing
Size the new platform, design storage and networking, set RPO/RTO and rollback criteria.
Pilot migration
Migrate a small low-risk set end-to-end and validate the runbook.
↳ Export tables to GCS as Parquet; load into ClickHouse; convert Standard SQL; re-point dashboards; validate.
Production migration
Move workloads in scheduled waves using automation; verify after each wave.
Validation & optimization
Tune performance, confirm backup/DR, and update monitoring and docs.
Decommission source
Reclaim licenses, retire old infrastructure, and capture lessons learned.

Tooling & automation

Export tables to GCS as Parquet; load into ClickHouse; convert Standard SQL; re-point dashboards; validate.

OffVendor's wizard pre-fills these scripts with your environment — inventory export, disk/schema conversion, bulk provisioning, and validation.

Frequently asked

Is migrating from Google BigQuery to ClickHouse worth it?

For most teams facing rising Google BigQuery costs, yes — ClickHouse (free oss / cloud) typically lowers 3-year total cost of ownership, though the right answer depends on workload complexity and in-house skills. Use the calculator to model your own numbers.

How long does a Google BigQuery to ClickHouse migration take?

A typical mid-size estimate is around 15 weeks across six phases — discovery, design, pilot, waved production migration, validation, and decommission. Larger or more complex estates take longer.

What tools are used to migrate from Google BigQuery to ClickHouse?

Export tables to GCS as Parquet; load into ClickHouse; convert Standard SQL; re-point dashboards; validate.

Get a vendor-accurate ClickHouse quote

A guided builder that turns your estimates into a requirements report you can send to a vendor, partner, or distributor to secure a binding quote.

How this works — and what's yours to provide
  • Your inputs, your responsibility. The figures and estimates here describe your environment and requirements — please make sure they're accurate. OffVendor's defaults are illustrative starting points only, not vendor pricing.
  • It generates a requirements report (RFQ). Use it to capture your sizing and requirements and share it with your authorized vendor / partner / distributor to obtain a final, binding quote.
  • Then close the loop on your TCO. When the real quote comes back, plug those actual prices into the calculator above to refine your TCO and see where reality differs from the estimate.
  1. 1Size it
  2. 2Requirements
  3. 3Your details
  4. 4Channels & export

How big is your Google BigQuery estate?

Sum your usable array capacity, or the total front-end data you protect. Not sure? Enter rough numbers — the distributor confirms exact counts later.

200 TB managed
Default mid-size assumption (200 TB managed)
Estimates are illustrative and configurable; production figures come from vendor list prices and your own quotes.