Database Read/Write Cost Calculator
Estimate the monthly cost of a pay-per-operation database from your read and write operation counts, their unit prices and stored data volume.
How it works
Read cost = (reads ÷ 1M) × read price · Write cost = (writes ÷ 1M) × write price · Storage = GB × $/GB-mo · Total = read + write + storage
Pay-per-operation databases meter reads and writes separately, and writes usually cost several times more than reads because they must be durably persisted and replicated. On read-heavy apps the read line dominates volume but the pricier write rate can still make writes a big share of the bill. Storage is a steady per-gigabyte charge that grows with your data over time — cutting operation counts with caching or batching is where the fast savings are.
Worked example
Fifty million reads at $0.25/M is $12.50, ten million writes at $1.25/M is $12.50, and 50 GB at $0.25/GB-mo is $12.50 — a total of $37.50 a month, split evenly across the three lines in this example.
Frequently asked questions
Why are writes more expensive than reads?
A write has to be durably stored and often replicated to multiple nodes before it is acknowledged, which is more work than serving a read from an existing copy. That extra durability cost is why per-operation write pricing typically runs several times the read rate.
How can I lower read costs?
Cache frequently read data in memory or at the edge so repeat requests never hit the database, and batch or paginate queries to avoid over-reading. On strongly consistent stores, using eventually consistent reads where acceptable is often billed at a lower rate.
Does one query equal one operation?
Not necessarily — a single query can consume many read units depending on how many items or how much data it scans, and indexes add their own write costs. Check how your provider counts operations (per item, per KB, or per request) before mapping your query volume to these units.
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This calculator is for educational purposes. Double-check important results before acting on them.