Google Cloud Next ‘26 was a whirlwind. With two booths, one on the main expo floor and one in the Activation Alley upstairs, the Rabbit team spent three days in constant conversation with the global Google Cloud community.

Between the high-energy keynotes and the incredible activations, one thing became crystal clear: The world loves BigQuery, but they’re struggling to manage it.

The BigQuery Paradox: Powerful yet Painful

The most common sentiment we heard from teams—whether they were small startups or global enterprises—was a version of this:

“We really love BigQuery and how powerful it is, but it can just be so damn difficult to use efficiently.”

BigQuery is arguably the best data warehouse on the market, but the barrier to efficiency is high. We spoke with dozens of teams who are stuck on On-Demand pricing simply because the leap to Reservations feels too complicated. On the flip side, teams already using Reservations admitted they are often over-provisioning just to stay safe, leading to significant waste.

Learn all about BigQuery Editions and Reservations. Download our white paper:

”We don’t have the bandwidth”

We met leads who are seeing their cloud bills skyrocket, with one prospect noting:

“We’re spending $100,000 a month on this thing, but our team doesn’t have the time to implement any sort of cost-saving strategy.”

That is the “Complexity Gap”: companies have the desire to be cost-efficient, but they lack the engineering bandwidth to manually fine-tune their environments. The recurring question we faced was: “If we implement Rabbit, will it affect our performance? Is there going to be any latency?”

The answer is why we saw so much traffic at our booths: Rabbit optimizes both costs and performance, without the toil. By automating the right-sizing of workloads in the background, we allow teams to keep their performance benchmarks while slashing their bills. Ninja Van’s case study is a good example of how Rabbit’s optimization can contribute to significant infrastructure performance improvement – while driving down bills.

As one attendee put it:

“If we can set this up and let it run in the background, I don’t see any reason why anybody else wouldn’t use your platform.”

One of the most popular draws at both of our booths was our BigQuery Savings Calculator. We had a steady stream of curious leads stopping by to plug in their current spend and reservation data. The reactions were almost always the same: a mix of surprise and immediate curiosity. When people saw the potential for 30% to 50% savings pop up on the screen, the follow-up question was always, “How exactly do you drive those results without slowing us down?”

It was a great opportunity to show—rather than just tell—how Rabbit’s automation tackles the “Autoscaler Tax” and handles the heavy lifting that teams simply don’t have the bandwidth to do manually. That’s why companies like Nordstrom, Lufthansa Group, Servier & more chose to optimize with Rabbit.

Watch this conversation at Next between Nordstrom’s Bryce Ageno and Rabbit’s Balazs Molnar as they discuss automated BigQuery optimization that helped Nordstrom cut their BigQuery costs by 47%, and the way forward: shift-left FinOps and how cloud efficiency can help fund AI initiatives, making AI spend economical and ROI-backed, and use AI to run that loop: