Estimated Query Cost Result
Results appear below the header and above the calculator form, exactly where analysts usually compare scenario outputs.
Calculator Inputs
Example Data Table
The table below uses the page defaults as a realistic analytics workload example.
| Item | Example Value |
|---|---|
| Data Scanned Per Query | 120.00 GB |
| Scan Price | $5.00 per TB |
| Average Runtime | 45.00 seconds |
| Compute Units | 8.00 |
| Queries Per Day | 350 |
| Working Days | 22 |
| Cache Hit Rate | 28.00% |
| Retry Overhead | 4.00% |
| Optimization Savings | 12.00% |
| Total Monthly Cost | $3,531.93 |
| Cost Per Query | $0.4410 |
| Annual Cost Projection | $42,383.12 |
Formula Used
This calculator combines scan pricing, compute time, storage reads, network transfer, retries, tuning gains, and fixed platform overhead into one estimate.
Effective Runs Per Day = Queries Per Day × (1 + Retry Rate ÷ 100) Monthly Query Runs = Effective Runs Per Day × Working Days Per Month Effective Scan Per Run = Data Scanned × (1 − Cache Hit Rate ÷ 100) × (1 − Optimization Savings ÷ 100) Scan Cost = (Effective Scan Per Run × Monthly Query Runs ÷ 1024) × Scan Price Per TB Compute Cost = (Runtime Seconds ÷ 3600 × Compute Units × Monthly Query Runs × (1 − Optimization Savings ÷ 100)) × Compute Price Per Hour Storage Read Cost = (Storage Reads Per Day × Working Days ÷ 1024 × (1 − Optimization Savings ÷ 100)) × Storage Read Price Per TB Egress Cost = Egress GB Per Day × Working Days × Egress Price Per GB Total Monthly Cost = Scan Cost + Compute Cost + Storage Read Cost + Egress Cost + Fixed Monthly Platform Cost Cost Per Query = Total Monthly Cost ÷ Monthly Query RunsHow to Use This Calculator
- Enter the average data scanned by one query in gigabytes.
- Provide pricing for scanned data, compute time, storage reads, and egress.
- Add workload volume using queries per day and working days per month.
- Set cache hit rate, retry overhead, and optimization savings to match real behavior.
- Include any fixed monthly charge for reservations, monitoring, or shared platform overhead.
- Press Calculate Query Cost to show the estimate above the form.
- Review the breakdown table and Plotly chart to compare cost drivers.
- Use the CSV and PDF export buttons to save the scenario for reporting or budgeting.
FAQs
1) What does this calculator estimate?
It estimates monthly and annual analytics query cost using scan volume, compute usage, retries, caching, storage reads, network egress, and fixed platform charges.
2) Why include cache hit rate?
Cache hits reduce billable scanned data and often shorten runtime. Modeling cache rate helps compare warm-cache workloads against first-run or uncached behavior.
3) What is the difference between scan cost and compute cost?
Scan cost is tied to data read, usually priced per terabyte. Compute cost reflects warehouse, slot, or engine time consumed while queries execute.
4) Should retry overhead be included?
Yes. Failed jobs, timeout retries, and orchestration reruns can materially increase monthly spend. Even a small retry percentage improves budgeting realism.
5) Does optimization savings affect every component?
In this model, optimization savings reduce scanned data, runtime, and storage reads. Adjust it to reflect pruning, clustering, indexing, or SQL tuning.
6) Can this be used for any analytics platform?
Yes, as long as you map your platform’s billing units into the provided rates. Enter your local price-per-terabyte, compute rate, and transfer charges.
7) Why is cost per query useful?
It helps benchmark teams, compare workloads, and spot inefficient dashboards or pipelines. Rising cost per query often signals poor caching or oversized compute.
8) Are these results identical to vendor invoices?
No. Results are planning estimates, not vendor invoices. Final bills can differ because of minimum charges, rounding, burst pricing, free tiers, and reservations.