ClickHouse vs Google BigQuery
Both are alternatives to Snowflake. Here's how they stack up — verified facts, no spin.
Also searched as Google BigQuery vs ClickHouse — same comparison, one verdict.
ClickHouse is open source (Apache-2.0) and Google BigQuery is not (Proprietary (hosted service)) — so the real question is whether you want to own the data warehouses & analytics engines stack or rent it.
ClickHouse
TOP PICKAnalytical queries at a speed that reframes what you thought was slow.
ClickHouse is a columnar database built for analytical queries and it is startlingly fast — billions of rows scanned in under a second on modest hardware is routine rather than exceptional. Apache-2.0, around 49k stars, and used at scale by Cloudflare, Uber and many others. Compression is excellent, so storage costs fall as well as compute. It is the strongest technical answer on this page, and the cost is operational: schema and index design matter enormously here, and a badly designed table is slow in ways a warehouse would have hidden from you.
Google BigQuery
Serverless warehousing with no cluster to size — if you are already on GCP.
BigQuery is fully serverless: there is no warehouse to start, stop or size, you write SQL and Google works out the compute. On-demand pricing is roughly $6.25 per terabyte scanned, so a well-partitioned table can be very cheap and an unpartitioned `SELECT *` can be alarming. Included here because for a team already inside Google Cloud, the honest comparison is not open versus proprietary but which proprietary — and BigQuery's operational simplicity genuinely beats Snowflake's for infrequent workloads.
Side by side
10 points of comparison, every one read from a verified field. Green marks the side that wins a row outright. A dash means we do not hold that fact — never that it is zero.
| ClickHouse | Google BigQuery | |
|---|---|---|
| Sovereignty ScoreOur transparent 0–100 composite for data ownership and exit cost. | 93 | 32 |
| Open source | Yes | No |
| Self-hostable | Yes | No |
| Local-first data | Yes | No |
| License | Apache-2.0 | Proprietary (hosted service) |
| Pricing | Free and open source. ClickHouse Cloud is a paid managed option. | About $6.25 per TB scanned on demand, or flat-rate capacity. Storage around $20/TB/month. Checked 2026-08-03. |
| RAM to run it wellThe figure that actually matters, not the vendor's minimum. | 16 GB | — |
| Realistic running costWhat the box costs each month if you run it yourself. | $80–150/mo for a single node handling tens of billions of rows, against thousands on Snowflake for comparable workloads | — |
| Setup timeHonest first-install estimate, not the marketing quickstart. | Half a day for a single node; a real cluster is a project | — |
| Ongoing maintenanceThe part nobody budgets for. | Moderate. Schema and ORDER BY decisions are close to permanent, merges need disk headroom, and upgrades want testing. | — |
ClickHouse is Macrostack's recommended Snowflake alternative, so it's our pick here.
ClickHouse
Strengths
- +Frequently outruns Snowflake on analytical workloads, at a fraction of the cost
- +Apache-2.0 with no enterprise carve-out
- +Excellent compression — storage bills drop noticeably
- +Proven at enormous scale by well-known operators
Trade-offs
- −Schema and index design matter far more than in a warehouse
- −Updates and deletes are awkward by design
- −Operating a cluster is real work
- −Weaker governance and lineage tooling than Snowflake
Google BigQuery
Strengths
- +Genuinely serverless — nothing to size, start or stop
- +Cheap for infrequent queries against well-partitioned data
- +Native integration with the Google Cloud and Workspace estate
- +Strong ML and geospatial support built in
Trade-offs
- −Proprietary, hosted, and deepens Google Cloud lock-in
- −Scan-based pricing punishes careless queries severely
- −Egress costs make leaving expensive
- −Practically requires you to be on GCP already
Which one fits you
The trade-offs above, turned into a decision. Find the line that describes your team.
Choose ClickHouse
if you want the source and the option to fork it, and you would rather run it on your own hardware, and your data should stay on machines you control.
Choose Google BigQuery
if genuinely serverless — nothing to size, start or stop.
Neither, yet
if both carry a real cost you should weigh first — schema and index design matter far more than in a warehouse, and proprietary, hosted, and deepens Google Cloud lock-in. If either of those is a dealbreaker for your team, the shortlist is wrong rather than the choice.
What it takes to run these yourself
Real requirements and honest running costs, not the vendor quickstart.
ClickHouse vs Google BigQuery — common questions
Is ClickHouse a better fit than Google BigQuery for data warehouses & analytics engines?
It depends on what you are optimising for, and the honest split is this: ClickHouse scores 93 to Google BigQuery's 32 on data ownership and exit cost, so it is the safer choice if you care about being able to leave. Google BigQuery earns its place on a different axis — genuinely serverless — nothing to size, start or stop. Neither is a wrong answer for every team; the table above is the actual comparison.
What happens if we want to switch later?
ClickHouse keeps its data local or in open formats, so leaving is an export rather than a negotiation. Google BigQuery keeps your data on its own infrastructure, which is the part to plan for: confirm the export path before you commit, not when you are already trying to leave.
Is ClickHouse free?
ClickHouse: Free and open source. ClickHouse Cloud is a paid managed option.. The other side of this comparison, Google BigQuery, is priced as About $6.25 per TB scanned on demand, or flat-rate capacity. Storage around $20/TB/month. Checked 2026-08-03.. "Free" here means no licence fee — if you self-host it you still pay for the server, and the running cost row above is our honest estimate of that.
Can I self-host ClickHouse?
ClickHouse can be self-hosted; Google BigQuery cannot, so it stays on the vendor's infrastructure whatever you do.
Are ClickHouse and Google BigQuery both alternatives to Snowflake?
Yes — both appear in our Snowflake comparison, which is why they are worth putting side by side. People usually arrive here already having decided to move off Snowflake and now choosing between the two replacements, which is a narrower and much easier question.
Related alternative guides
Facts verified 2026-08-03. Licenses and pricing change — spotted something out of date? That's a correction we want.