Real ChatGPT answer · index seedkGGgTSwpnzocompleteB2B software · data and analytics platformscomparison
We need to speed up heavy aggregations across millions of rows in PostgreSQL. Would migrating to ClickHouse solve our latency issues or should we just add better indexes?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
We need to speed up heavy aggregations across millions of rows in PostgreSQL. Would migrating to ClickHouse solve our latency issues or should we just add better indexes?
2 real searches · 1 real-search pass
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 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
PostgreSQL documentation EXPLAIN ANALYZE buffers indexes index-only scans materialized views partitioning aggregation performance Google ↗
ClickHouse documentation columnar storage GROUP BY aggregation performance MergeTree materialized views Google ↗
- When should you use a columnar database? · clickhouse.com
- How columnar storage works · clickhouse.com
- The definitive guide to ClickHouse query optimization (2026) | Engineering | ClickHouse Resource Hub · clickhouse.com
- PostgreSQL: Documentation: 18: 14.1. Using EXPLAIN · postgresql.org
- Index-only scans · wiki.postgresql.org
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
PostgreSQL documentation EXPLAIN ANALYZE buffers indexes index-only scans materialized views partitioning aggregation performance OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
ClickHouse documentation columnar storage GROUP BY aggregation performance MergeTree materialized views OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |