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Rabbit Solutions

One platform for BigQuery optimization, built for every role

The BigQuery optimization brain for your organization: shift-left for engineers, estate-wide autopilot for platform leaders, and commitment planning, anomaly detection, and attribution for FinOps.
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Who it's for

For the teams that run BigQuery

Manual BigQuery tuning breaks differently for every team. Start with the friction you feel most.

Data Platform Leaders

01

Put BigQuery optimization on autopilot.

Continuous tuning across every project and team, engineering guardrails in the workflow, and drift visibility before stakeholders escalate. Recommendations by default; automation inside the policies you set.

47% BigQuery spend ↓ at Nordstrom · 400+ engineering hours/month reclaimed

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Data Engineers

02

Ship more efficient BigQuery pipelines faster.

Cost-aware code review and SQL cost estimation on every change, always-on optimizers that cut tuning toil, and contention signals that point to the job, not a vague ticket.

400+ engineering hours/month reclaimed · cost on every PR

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FinOps & Finance

03

Rightsize commitments. Catch anomalies early. Attribute every dollar.

Commitment planning from real usage, near real-time anomaly detection, and finance-ready attribution with caps and automated micro-commitments inside the guardrails you approve.

20-50% savings from rightsized commitments · Lufthansa 52% total BQ cost ↓

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bigquery optimization platform

Rabbit platform

Every Solutions path runs on the same underlying platform. Rabbit's Automate, Observe, Build, and Govern feature sets work together as one system, tuning one lever without the others leaves savings on the table.

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Automate

01

Always-on optimizers tune slots, pricing, storage, reservations, caching, and SQL within your guardrails.
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Observe

02

Deep observability into cost and performance, from account rollups to individual jobs, near real-time.
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Build

03

Shift-left cost review and SQL cost estimation in PRs, IDEs, and AI agent sessions.
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Govern

04

Commitment planning, hard spend caps, and attribution, even on reservations.
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Automate

01

Always-on optimizers tune slots, pricing, storage, reservations, caching, and SQL within your guardrails.
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Build

03

Shift-left cost review and SQL cost estimation in PRs, IDEs, and AI agent sessions.
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Observe

02

Deep observability into cost and performance, from account rollups to individual jobs, near real-time.
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Govern

04

Commitment planning, hard spend caps, and attribution, even on reservations.
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Explore the platform

Not sure where to start?

Book a demo and we'll show you exactly where your BigQuery estate is leaving money on the table.

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Calculate your savings

FAQ

Our Solutions pages frame the same Rabbit platform for different roles: data platform leaders, data engineers, and FinOps and finance. Each page starts from that team's problem, shows which Rabbit capabilities help, and links to proof and a demo. Pick the path that matches your job — you do not need a separate product per persona.

Platform leaders who own estate-wide cost, performance, and policy should start with Data Platform Leaders. Engineers who write and review BigQuery SQL should start with Data Engineers. Finance and FinOps teams who plan commitments, catch anomalies, and attribute spend should start with FinOps & Finance.

Platform pages describe what Rabbit does by capability: its Automate, Observe, Build, and Govern feature sets. Solutions pages describe who Rabbit is for and which outcomes matter first. Use Solutions to route by role; use Platform to go deep on any capability.

Not in Phase 1. An AI Teams path is planned for a later phase. Until then, engineers using coding agents should start with Data Engineers (Context Engine and cost-aware review) or Build on the platform.

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.
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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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