The best cloud data warehouses, according to hackers
9 cloud data warehouses were recommended on Hacker News between November 2025 and November 2026. We rank them by how many separate people recommend each one, and 3 earn the Hacker Approved badge.
Top picks
The three most recommended cloud data warehouses with the badge. Each figure is 2 people. RecommendsCriticizes One comment
Managed, no infrastructure to run
People recommend BigQuery for big SQL analytics without running infrastructure, and it has a free tier. The most common caveat is query cost, which can run up large bills.
Fast on analytical workloads
A fast, extensible Rust query engine that people build databases and analytics tools on. The common caveat is that it is not a full embedded database and lacks indexes and transactions.
Simple SQL over S3 data
People recommend Athena for querying data in S3 without running servers, with simple SQL and little setup. Critics say it lags other query engines on features and file formats.
All 9 cloud data warehouses, ranked
Select a column heading to sort. Approval share is recommenders out of everyone who gave an opinion; the tick on each bar marks the 2 to 1 line the badge needs. Months counts the months, out of 13, in which someone recommended it.
| Rank | |||||||
|---|---|---|---|---|---|---|---|
| 1 | Palantir | 86 | 613 | 12% | 12 | — | — |
| Tied 2 | Snowflake | 26 | 24 | 52% | 12 | — | — |
| Tied 2 | Google BigQuery | 26 | 9 | 74% | 10 | — | Approved |
| 4 | Palantir Foundry | 21 | 31 | 40% | 8 | — | — |
| 5 | Databricks | 20 | 20 | 50% | 10 | — | — |
| 6 | Apache DataFusion | 17 | 3 | 85% | 8 | — | Approved |
| 7 | Amazon Athena | 13 | 6 | 68% | 8 | — | Approved |
| 8 | Palantir Gotham | 6 | 29 | 17% | 4 | — | — |
| 9 | MotherDuck | 5 | 3 | 63% | 4 | — | — |
How we rank
Rank is the number of separate people who recommend a product in a Hacker News comment over the past year. Someone who praises the same cloud data warehouse in five threads counts once.
The badge goes to cloud data warehouses that at least 10 people recommend, with recommenders outnumbering critics at least 2 to 1, recommended in at least 4 of the 13 months.
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