Estimate BigQuery costs for on-demand and Editions pricing with storage tiers, streaming inserts, and break-even analysis.
Last verified: April 2026
First 1 TB/month free. $6.25 per TB after that.
$0.02/GB-month
$0.01/GB-month (90+ days untouched)
$0.012 per 200 MB (min 1 KB/row)
$1.10 per TB read
Output will appear here...The BigQuery Cost Estimator calculates monthly Google BigQuery costs for both on-demand and Editions (Standard, Enterprise, Enterprise Plus) pricing models. It factors in storage costs for active and long-term data, query compute costs by bytes scanned or slot-hours consumed, streaming insert fees, and Storage API read charges. The tool includes a break-even analysis that shows when switching from on-demand to Editions flat-rate pricing becomes more economical based on your query volume. It is the go-to calculator for data analysts and engineers planning BigQuery deployments at any scale.
Your data team runs 200 queries per day averaging 50 GB scanned each — roughly 300 TB per month at $1,875 on-demand. The estimator shows that 200 Enterprise Edition slots on a 1-year commitment would cost $1,200/month and handle the same workload with room to spare. You switch to Editions and save $675/month. Six months later, a new ML pipeline adds 500 GB/day of scans — on-demand would have jumped to $3,000/month, but the slot reservation absorbs it with no additional cost.
Slot reservations (via Editions) break even with on-demand at roughly 500 GB of data scanned per slot per month. If your team scans less than that, on-demand is cheaper. But if a single analyst runs a SELECT * on a 10 TB table, that's $62.50 in one query on on-demand — a slot reservation would have absorbed it. Model your worst-case query, not just your average.
Partitioning and clustering are the most impactful cost optimization for on-demand pricing. A query on a table partitioned by date that filters to one month scans 1/12th the data. Add clustering on a high-cardinality column and you can reduce scanned bytes by 95%+. The estimator helps you model the difference, but implement partitioning before worrying about slots.
BigQuery's free tier (1 TB queries, 10 GB storage per month) is per-billing-account, not per-project. If you have 20 projects in one billing account, they share that 1 TB. Teams often assume each project gets its own free tier and are surprised by the first bill.
The estimator models BigQuery costs across two dimensions: storage (active data at per-GB rate, long-term data at discounted rate, streaming buffer at per-GB rate) and compute (on-demand at per-TB-scanned rate, or Editions at per-slot-hour rate with commitment discounts). For on-demand, it multiplies estimated bytes scanned by the per-TB price. For Editions, it calculates slot-hours based on concurrency and query duration, applying autoscale, 1-year, or 3-year commitment pricing as selected.
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