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Rabbit Platform · Govern

Govern BigQuery spend with caps, commitments, and attribution

Rabbit helps FinOps teams plan BigQuery commitments more precisely and allocate cost accurately, even on reservations. Budgets and hard caps keep spend under control.
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20–50%

savings from rightsized commitments

-20%

cost anomalies

100%

of costs mapped to business units

inside govern

Planning, enforcement, and reporting as one system

Caps without attribution leave finance blind. Commitments without guardrails still surprise you on the bill. Rabbit governs spend across planning, enforcement, and reporting as one system.

Budget and hard caps

Set spend limits by user or label, and block or warn on queries that exceed a safe cost threshold.

On reservations, Rabbit estimates slot-based query cost in advance so caps work before a job runs. BigQuery can't natively forecast those costs.

  • Daily, weekly, and monthly budgets per user or label

  • Slot-based query cost estimation on capacity pricing

  • Set safe limits for queries (block jobs estimated above a set threshold)

20% fewer cost anomalies

Commitment planning

Rightsize slot and spend commitments from real usage, and lift coverage with weekly micro-commitments instead of one large lock-in.

Rabbit's BigQuery Commitment Planner models slot and spend commitments together, and Committed Use Discount (CUD) Automation purchases small weekly batches so coverage rises without over-committing.

  • BigQuery Commitment Planner across slot and spend commitments

  • CUD Automation: weekly micro-commitment purchases

  • Gradual coverage lift without long-term lock-in

20-50% savings from rightsized commitments

Rabbit Labels

Map virtual labels from projects and existing GCP labels so spend rolls up to business units, teams, or any dimension finance needs.

Rabbit Labels turn raw project and label metadata into shared cost allocation views: chargeback, showback, and cross-project reporting without re-tagging every pipeline.

  • Virtual labels mapped from projects and GCP labels

  • Shared cost allocation across business units

  • Pairs with label-level insights and anomalies in Observe

100% of costs mapped to business units

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Safety & Reliability

Guardrails finance can trust

Rabbit gives FinOps and platform teams shared control. You set the policies, Rabbit enforces them against live BigQuery usage. For certifications, residency, and how Rabbit handles access, see Security.

Caps as guardrails

Hard limits stop runaway spend without shutting down normal workloads. Tune by user, label, or query threshold.

01

Commitments on your terms

Micro-commitments raise coverage gradually. You approve automation paths before Rabbit purchases.

02

Attribution you can defend

Virtual labels roll up spend for chargeback and showback without re-tagging every job by hand.

03

Solutions

For the teams that run BigQuery

Same platform. Different priorities. Pick the path that matches your role.

Data Platform Leaders

Rightsized commitments, spend guardrails, and attribution finance can act on.
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Data Engineers

Query-level cost estimates and caps that catch expensive jobs before they run.
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FinOps & Finance

Plan commitments, enforce caps, and map every BigQuery dollar to the business.
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See how Rabbit would govern your BigQuery spend

Start with a metadata-only assessment. See where commitments are misaligned, where guardrails could help, and how spend maps to your business.

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Calculate your savings

FAQ

Rabbit's Govern feature set gives platform and finance teams shared controls for BigQuery: rightsizing commitments, hard spend caps by user, label, or query, and attribution with virtual labels and shared cost allocation. Policies are implemented and enforced against live usage, not only reported after the fact.

On reservations, BigQuery does not natively forecast per-query cost the way on-demand bytes scanned does. Rabbit estimates slot-based query cost in advance so daily, weekly, and monthly budgets, plus query-level thresholds, can warn or block before an expensive job runs.

Rabbit's BigQuery Commitment Planner models slot and spend commitments from real usage. Committed Use Discount (CUD) Automation can purchase weekly micro-batches so coverage rises gradually instead of one large lock-in. Projected savings from rightsized commitments are commonly in the 20-50% range.

Rabbit Labels map virtual labels from projects and existing GCP labels so BigQuery spend rolls up to business units, teams, or other finance dimensions. That supports chargeback and showback across projects without re-tagging every pipeline by hand, and pairs with label-level insights in Observe.

Not without your approval path. Micro-commitments can raise coverage gradually, and you approve automation before Rabbit purchases. Caps, planners, and attribution are controls you configure. Rabbit enforces the policies you set against live BigQuery usage.

No. Rabbit is a BigQuery optimization platform with FinOps capabilities for commitments, caps, and attribution. Finance and platform teams share Govern features alongside Automate, Observe, and Build, rather than using Rabbit as a generic multi-cloud FinOps category product.

You set the policies; Rabbit enforces caps, commitments, and attribution against live BigQuery usage. For certifications, residency, and access detail, see Enterprise security.
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We help data teams cut BigQuery costs by 32% on average and see exactly where every slot hour goes.
The autonomous engine for BigQuery cost and performance
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