Compare the pricing models of Supabase and Firebase specifically focusing on edge functions and vector database storage costs for an AI-powered SaaS tool.
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Compare the pricing models of Supabase and Firebase specifically focusing on edge functions and vector database storage costs for an AI-powered SaaS tool.
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.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Supabase pricing Edge Functions compute invocations included usage vector embeddings pgvector database storage pricing 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
Firebase pricing Cloud Functions 2nd gen invocations compute networking Firestore vector search storage index pricing 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 |