Built for BigQuery only
No other warehouse, no detour. Every recommendation speaks fluent slots, reservations, Bi-Engine, logical vs physical storage.
The only pure-play BigQuery FinOps
Biq Blue is the only FinOps tool built exclusively for Google BigQuery. Not a multi-cloud dashboard. Not a generic spend tracker. Storage mode, reservations, clustering, Bi-Engine: every recommendation is BigQuery-native.
Move 249,887 queries of app-live-prod from on-demand to slot reservations.
Run project-big-mama, metabase-prod, app-green-lake, app-sea-lion in an autoscaling reservation.
Setup reservation →Be alerted to cost anomalies within the hour before they spiral.
Enable alerts →Biq Blue v2.4.1 FinOps for BigQuery · Org acme-data · 12 projects > Hi Biq, can you tell me how to optimize my BigQuery? ● I'll scan your INFORMATION_SCHEMA across 12 projects. ✻ Scan(metadata · jobs · reservations) └ Done (2.3M queries · 4,812 tables · 28s) ✻ Thinking… (esc to interrupt) ● Recommendations · $4,318/mo in cuts ─ switch 3 datasets to PHYSICAL storage −$2,092 ─ delete 24 unused tables (1.8 TiB) −$196 ─ move 9,539 on-demand queries to slots −$858 ─ cluster ord_2024_* on user_id −$412
Trusted by data teams at
No other warehouse, no detour. Every recommendation speaks fluent slots, reservations, Bi-Engine, logical vs physical storage.
Not "optimize your queries." Exactly which 24 tables to drop, which 9,539 queries to move to reservations.
Biq Blue only reads INFORMATION_SCHEMA. Your data never leaves your BigQuery project. Ever.
Pure-play advantage
Because we only do BigQuery, we see what multi-cloud tools miss. Break down spend by service, user, project, label, or reservation, and find the one scheduled job that's quietly costing you $1,400 a month.
Recommendations
Every recommendation comes with an exact savings number, the queries or tables affected, and a one-line action. No dashboards to interpret.
These 9,539 queries of app-live-prod would be $858 cheaper
using flat-rate instead of on-demand.
24 tables totaling 1.8 TiB have not been queried in 90 days.
Safety by design
We only query INFORMATION_SCHEMA. All state lives in a dataset in
your project. Revoke the service account and Biq Blue is gone: no export,
no residue, no lock-in.
From customer Slacks
Wrap up 2025
In 2025, BigQuery (+ GCS, we include it since we keep a bunch of archived tables there) cost us $903K, vs $1,484K in 2024 😊 Monthly costs are now around ~$60K — we're back to December 2022 levels. Mostly thanks to @Biq 🚀
Hello, FYI — I let it run all Sunday on the slot setup and we went from $128 $118 → $38
daily on the 2 jobs (hourly/trihourly) 👏
−$90/day, that's it ?
It's $118 above actually, $80/day → $2,400/month 👍
Awesome!
Vendor paid for itself already 👏
Hi @Bruno & @Nicolas, hope you had a great holiday break.
We rolled out reservations and we're tracking usage on this board: myaccount.biq.blue/analysis_reservations.html
The goal is to right-size each reservation per batch type to maximize utilization, based on overnight runs. Would it be possible to filter on today's date only, to track the reservation usage ratio and check the caps are optimal?
Hi @Julien, thanks! Hope you had a great break too 🎄
Solid work on your end! What you saved by switching to reservations is
on-demand cost − reservation cost:
(266+315+12+55+37) − (117+131+5+10+5) = 685 − 268 = $417/week
=> You'll save around $1,200/month, or $14,000/year 💥
If we zoom in here, moving 1,172 on-demand queries ($62) onto the reservation ($10) is 6× cheaper — that's $1,500/month less 🥳
It's beautiful 😍
@Nicolas Good news — you just helped us avoid a nice $$$ incident thanks to alerting 🙏
(edited)Very cool! Maybe we'll put that line in future testimonials haha
not unhappy I set up alerting this morning 😂😅
💰 More precision on the costs → it's really better 😉
Billed by GCP organization. Every tier ships every feature.
For small teams
Flat, per month · 1–30 BigQuery user(s)*
Start trialThe popular choice
Per user*, per month · 30+ BigQuery user(s)
Start trialBest value
Per user*, per month · 12-month commit, paid upfront
Talk to usPrices shown exclude applicable tax. Plans and prices are subject to change.
* A "user" is a distinct Google BigQuery user_email active during
the month.
It cross-references job, table, reservation and storage data from INFORMATION_SCHEMA to
produce precise savings recommendations.
No. Only the INFORMATION_SCHEMA views and a dedicated dataset in your project. Nothing
leaves your house.
Four minimal roles — three read-only org-wide, one write-access on a single dataset we create in your
project.
On your main project · BigQuery Data Editor (on the dedicated Biq Blue dataset only)
At organization / folder / project level · BigQuery Metadata Viewer ·
BigQuery Resource Viewer · BigQuery Job User
That's all. No data access, no admin, no billing. Revoke the service account and we're gone.
Our customers generate −40% average savings within the first two weeks.
30-minute setup. First month free. No credit card.
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