ClickHouse vs Trino
Both are alternatives to Snowflake. Here's how they stack up — verified facts, no spin.
Also searched as Trino vs ClickHouse — same comparison, one verdict.
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.
Trino
Query everything where it already lives, without moving any of it.
Trino is a distributed SQL engine that queries data in place — S3, Postgres, MySQL, Kafka, Elasticsearch — and joins across all of them in a single statement. Apache-2.0, around 13k stars, built by the team behind Presto. The point is that it removes the loading step entirely: no ingestion pipeline, no second copy, no drift between the warehouse and the source. That is a genuinely different architecture from Snowflake rather than a cheaper version of it, and it suits organisations whose data is scattered and will stay scattered.
Side by side
| ClickHouse | Trino | |
|---|---|---|
| Sovereignty Score | 93 | 91 |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Local-first | Yes | Yes |
| License | Apache-2.0 | Apache-2.0 |
| Pricing | Free and open source. ClickHouse Cloud is a paid managed option. | Free and open source. Managed options from Starburst and others. |
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
Trino
Strengths
- +Queries data where it lives — no ingestion, no second copy
- +Joins across completely different systems in one SQL statement
- +Apache-2.0 with a large connector ecosystem
- +Proven at very large scale
Trade-offs
- −A cluster to operate, with real memory tuning
- −Only as fast as the slowest underlying source
- −No storage of its own — it is an engine, not a warehouse
- −Java operations knowledge assumed
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Facts verified 2026-08-03. Licenses and pricing change — spotted something out of date? That's a correction we want.