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autonomous bigquery optimization

BigQuery cost and performance, continuously optimized

Rabbit covers every stage of BigQuery tuning: always-on optimization, deep observability, shift-left engineering, and FinOps control. Cost and performance improve together.
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bigquery optimization platform

How Rabbit works

Rabbit's pillars represent capabilities for different jobs on the same estate: keep production tuned, catch drift early, bring cost into building data pipelines, and give FinOps shared control. Start where your biggest opportunity is.

Brain illustration

Automate

01

Always-on optimizers tune slots, pricing, storage, reservations, caching, and SQL within your guardrails. Recommendations by default; automation when you opt in.

47% BigQuery spend reduction at Nordstrom · 40% improvement in performance

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Observe

02

Deep observability into BigQuery cost and performance. Drill from rollups to individual jobs, catch anomalies when spend diverges from forecast, and surface contention and slow queries before stakeholders complain.

Cost issues caught within hours, not days

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Build

03

Shift cost and performance left into development (IDEs, AI agents, and pull requests) so teams build optimized BigQuery pipelines from the first commit. Ready-to-merge optimization PRs when you opt in.

36% average cost waste caught before production

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Govern

04

Rightsize BigQuery commitments precisely based on real demand, even on reservations. Set hard spend caps by user, label, or query. Attribute every dollar back to the business with virtual labels and shared cost allocation.

20-50% savings from rightsized commitments

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Automate

01

Always-on optimizers tune slots, pricing, storage, reservations, caching, and SQL within your guardrails. Recommendations by default; automation when you opt in.

47% BigQuery spend reduction at Nordstrom · 40% improvement in performance

Learn more

Observe

02

Deep observability into BigQuery cost and performance. Drill from rollups to individual jobs, catch anomalies when spend diverges from forecast, and surface contention and slow queries before stakeholders complain.

Cost issues caught within hours, not days

Learn more

Build

03

Shift cost and performance left into development (IDEs, AI agents, and pull requests) so teams build optimized BigQuery pipelines from the first commit. Ready-to-merge optimization PRs when you opt in.

36% average cost waste caught before production

Learn more

Govern

04

Rightsize BigQuery commitments precisely based on real demand, even on reservations. Set hard spend caps by user, label, or query. Attribute every dollar back to the business with virtual labels and shared cost allocation.

20-50% savings from rightsized commitments

Learn more
Interconnected system

Tune one lever in isolation and waste shifts elsewhere

BigQuery levers interact. Autoscaler settings affect reservation utilization. Pricing affects slot consumption. SQL rewrites change storage and caching payback. Rabbit optimizes across levers so gains compound.

Brain illustration with labels: Slots, Storage space, Pricing model, Reservations, SQL Performance

Tuning runs in

AutomateArrow top right

•

Drift surfaces in

ObserveArrow top right

•

Automated rewrites ship via

BuildArrow top right

•

Policy lives in

GovernArrow top right
rollout

Getting started with Rabbit

Rabbit rolls out in stages.
Prove value in a free POC, then expand into automated optimization when you're ready.

01

02

03

04

05

SETUP

Native GCP API

Native GCP connection. No agents on your infrastructure. For how Rabbit handles access, certifications, and residency, see Security.

FREE POC

Risk-free trial

Run a 1–3 month free proof of concept with guaranteed ROI. Teams typically recover about 73% of Rabbit's first-year cost as savings during the free POC.

PROJECTED COST

Waste analysis

Once enough usage data is in, Rabbit shows where BigQuery spend and performance can improve so you can prioritize what to fix before broader automation.

ROI-BASED PRICING

Fund from savings

Rabbit's Pricing is tied to your cloud bill and the automated savings you realize. Customers see 4–10x ROI: you fund Rabbit from waste, not net-new budget. See Pricing.

OPTIMIZATION

Automated tuning

Opt into always-on optimizers and continuous savings inside your guardrails. Recommendations first; automation when you choose.

Safety & Reliability

Safe for production BigQuery at scale

You set the guardrails. Rabbit acts on production BigQuery automatically.

Performance protected

Slot optimizers and caching never trade speed for savings.

01

Recommendations first

Automation is opt-in, per optimizer and workflow.

02

SQL validated

Rewrites are tested on synthetic data for identical results before they're proposed.

03

See what Rabbit would do across your BigQuery environment

Start with a metadata-only assessment. See where cost and performance can improve first.

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Calculate your savings

FAQ

Rabbit is a unified platform offering comprehensive functionality for the full BigQuery lifecycle: Automate, Observe, Build, and Govern. Always-on optimization, deep observability, shift-left engineering, and FinOps controls work together so cost and performance improve as one system, not as isolated point fixes.

Native GCP integration with no agents on your infrastructure. Rabbit connects metadata-only, analyzes billing and job metadata, and returns projected cost impact so you can prioritize low engineering-effort opportunities before anything changes in production.

Automate continuously tunes BigQuery levers such as slots, pricing, storage, reservations, caching, and SQL within your guardrails. Govern plans commitments, enforces spend caps, and attributes spend with virtual labels so finance and platform share implemented policy, not only reports.

Observe surfaces cost and performance drift with drill-downs and alerts. From there, teams can opt into automation or ship individual validated fixes as reviewable pull requests. Detection stays metadata-only until you choose to implement optimizations.

No. Recommendations are the default. Automation and optimization PRs are opt-in, per optimizer and workflow. Slot optimizer and caching tuning is performance-protected so savings do not come from starving priority workloads. SQL rewrites are validated for identical results before they are proposed.

Rabbit is a BigQuery optimization platform with FinOps capabilities: commitment planning, spend caps, and attribution. FinOps teams use observability and governance functionality alongside engineering workflows, rather than treating Rabbit as a generic multi-cloud FinOps category tool.

Yes. Rabbit is a Google Cloud Partner, listed on Google Cloud Marketplace. Procurement can transact through your existing GCP vendor relationship instead of onboarding a new vendor, and the cost appears as a single line item on your GCP bill that counts toward committed Google Cloud spend.

Most teams run a 1-3 month free proof of concept. Connection is API-based after billing and metadata access are in place. Projected cost impact lands once enough usage data is available; time to first recommendations depends on billing history and estate size. Savings during the POC typically cover a large share of first-year Rabbit cost.
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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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