Repeated crawler requests can drive database work when each request triggers a query, but the title’s 22-day Postgres-hours story is an author-reported experience—not a verified benchmark. The Postgres provider, plan, crawler share, cache design, and before-and-after usage are not identified, so it cannot establish that crawlers caused the consumption or that moving to D1 fixed it.
The useful takeaway is to trace requests to database work before switching providers. Caching eligible repeat responses can avoid repeated execution; indexing can reduce the rows scanned on cache misses. Cloudflare D1 measures usage in rows read and written, not database hours.
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First verify that crawler requests are causing database usage
A high request count does not by itself show what is consuming database capacity. A crawler may request the same public page repeatedly, but only request-level logs connected to database activity can establish how much work those requests cause. A cache hit ratio alone cannot prove crawler attribution.
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For a 22-day account to be reproducible, the evidence would need to identify the Postgres vendor and plan, explain what its included “hours” mean and when they reset, and show dated usage or billing records. It would also need request logs that connect traffic to verified crawler user agents or IP ranges, plus the database usage before and after the change.
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Record the cache primitive, cache-key dimensions, time-to-live (TTL), invalidation or staleness policy, and handling of personalized or authenticated responses. These details determine which requests can share a cached response and whether that response remains appropriate to serve.
What Cloudflare D1 counts—and what it does not
D1’s documented Workers Free allowance is 5 million rows read per day, 100,000 rows written per day, and 5 GB total storage. The daily free limits reset at 00:00 UTC. These are Cloudflare’s published limits, not a measurement of the Postgres workload described in the headline. See Cloudflare’s D1 pricing documentation.
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D1 row reads are not simply the number of rows returned to an application. Cloudflare’s example says a full scan of a 5,000-row table counts as 5,000 rows read even if the query returns fewer. An unindexed filter may scan more rows than necessary; an appropriate index on the filtered field can reduce that scan. As a result, response size and request totals alone do not reveal D1 row-read usage. See the D1 FAQ.
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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →Cloudflare documents several ways to inspect row usage: the D1 meta object, GraphQL Analytics API, and dashboard. Use those metrics to examine usage by database and time period, then compare them with request logs. This can help distinguish heavy query scans from repeated requests that might be served from cache.
How response caching can reduce repeat database work
Cloudflare Workers Cache can serve an eligible cached HTTP response without running Worker code again. It supports GET and HEAD requests and uses response cache headers to decide whether a response can be stored. For a cacheable fresh URL receiving concurrent requests, Cloudflare documents request collapsing: one Worker execution can serve the waiting group rather than every simultaneous request triggering separate work. Details are in the Workers Cache documentation.
This can help when multiple requests for the same cacheable response would otherwise reach code that queries a database. It does not mean every crawler request becomes a hit: eligibility, freshness, URL and cache-key differences, and whether the response is personalized all matter. Nor does it prove a reduction in database usage without metrics showing fewer database reads or writes.
Workers Cache and the Cache API are different
Do not treat Workers Cache and the Cache API as interchangeable. Their documented behavior differs in cache scope and handling of concurrent requests.
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| Behavior | Workers Cache | Cache API |
|---|---|---|
| Can a hit avoid Worker execution? | Yes; an eligible cached HTTP response can be returned without running Worker code. | The request reaches Worker code, which uses the API to check or populate its cache. |
| Geographic scope and tiering | Cloudflare documents cache tiers. | Operations affect the cache in the data center handling the request; it does not support Tiered Cache. |
| Concurrent cacheable requests | Cloudflare documents request collapsing for concurrent requests to a fresh cacheable URL. | Concurrent requests are not collapsed. |
| Methods and response headers | Supports GET and HEAD; response cache headers determine whether responses can be stored. | Refer to Cloudflare’s cache architecture documentation for its scope and behavior. |
A Cache API response stored in one data center should not be described as globally present or as guaranteeing that requests from any geography will avoid Worker execution. Cloudflare explains this scope in its Workers cache architecture documentation.
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- Repeated requests for the same public response: assess whether a cacheable response can be reused, and choose a caching approach whose execution, scope, and concurrency behavior suit the traffic.
- High row reads when queries execute: inspect query plans and filters; an appropriate index may reduce rows scanned, including on cache misses.
- Personalized or authenticated pages: do not let different users share a response unless the cache key and policy safely separate their content.
- Suspected crawler load: correlate request logs with database metrics before assigning the cause. A usage reduction after caching does not, on its own, prove crawlers caused the original load.
Before comparing a Postgres plan with D1, establish the provider’s definition of “hours,” included allowance, reset rules, and the workload being measured. The headline does not name a Postgres provider or establish that the workload moved to D1; D1’s published row-based limits are not directly comparable to an unnamed hours-based plan.
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