Real ChatGPT answer · index seed3pqSS3WEsYwcompleteB2B software · data and analytics platformscomparison
Can you contrast the query optimization strategies used by Starburst Enterprise when querying distributed Trino against ClickHouse when running sub-second analytical queries on raw event data?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Can you contrast the query optimization strategies used by Starburst Enterprise when querying distributed Trino against ClickHouse when running sub-second analytical queries on raw event data?
3 real searches · 1 real-search pass
Starburst Enterprise Trino query optimization cost-based optimizer dynamic filtering pushdown fault tolerant execution official documentationGoogle ↗
OBSERVED
ClickHouse query optimization sparse primary index projections skipping indexes materialized views query pipeline official documentationGoogle ↗
OBSERVED
site:clickhouse.com/docs/en query optimization primary index ORDER BY projections skipping indexes materialized views PREWHERE parallel replicasGoogle ↗
OBSERVED
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 3 queries…
Searches and sources
ChatGPT3 real searches · gpt-6
Starburst Enterprise Trino query optimization cost-based optimizer dynamic filtering pushdown fault tolerant execution official documentation Google ↗
ClickHouse query optimization sparse primary index projections skipping indexes materialized views query pipeline official documentation Google ↗
site:clickhouse.com/docs/en query optimization primary index ORDER BY projections skipping indexes materialized views PREWHERE parallel replicas Google ↗
- Cost-based optimizations · docs.starburst.io
- Starburst · docs.starburst.io
- Pushdown · docs.starburst.io
- Starburst · starburstdata.github.io
- Dynamic filtering · trino.io
- Performance · starburst.io
- The definitive guide to ClickHouse query optimization (2026) | Engineering | ClickHouse Resource Hub · clickhouse.com
- Super charging your ClickHouse queries · clickhouse.com
- ClickHouse Feature Journey · clickhouse.com
- ClickHouse projections now behave like true secondary indexes · clickhouse.com
- ClickHouse Release 25.11 · clickhouse.com
- Top 10 best practices tips for ClickHouse · clickhouse.com
Queries
3 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Starburst Enterprise Trino query optimization cost-based optimizer dynamic filtering pushdown fault tolerant execution official documentation OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
ClickHouse query optimization sparse primary index projections skipping indexes materialized views query pipeline official documentation OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
site:clickhouse.com/docs/en query optimization primary index ORDER BY projections skipping indexes materialized views PREWHERE parallel replicas OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |