Cockroach Labs, the company behind distributed SQL database CockroachDB, is betting that the rise of agentic applications will make traditional database provisioning, where systems are sized for peak demand, increasingly difficult to justify as agents create highly concurrent, unpredictable and often short-lived database workloads that can leave provisioned compute idle between bursts.
Its solution to that problem is Cockroach Continuum, a database fleet management platform that pools compute and storage across isolated CockroachDB databases in an enterprise to allow capacity to be shared across workloads rather than reserved for individual systems.
That shared model can help enterprises accommodate sudden bursts of agent activity without maintaining dedicated infrastructure for every database, while paying only for consumption rather than peak capacity, the company said Tuesday.
Continuum does this by combining database virtualization with Cockroach Plenum, a feature that separates compute from storage so that the two capacities can scale independently.
It also draws on Cockroach Aegis, which uses an AI-assisted operations layer to diagnose issues and recommend actions across an enterprise’s database estate to help database administrators (DBAs) reduce the manual work involved in monitoring, troubleshooting and tuning databases while retaining control through policies, the company said.
That reduction in manual work for DBAs is likely to benefit CIOs in terms of operational cost.
“Enterprises don’t just pay for database capacity. They pay people to provision, monitor, tune, troubleshoot and scale these environments. If Cockroach can automate a meaningful portion of that work, there is value there and a chance to offset costs,” said Ashish Chaturvedi, executive research leader at HFS Research.
For more direct infrastructure-related cost savings via Continuum, though, CIOs will need to look at how their database estates are provisioned. Stephanie Walter, practice lead of AI stack at HyperFrame Research, said the greatest savings will come from large fleets of independently provisioned databases that spend much of their time underused: “Sharing capacity across workloads with different demand patterns could substantially improve utilization,” she said.
Not all enterprises will benefit: “Cost savings will be less meaningful for databases that already run near capacity or require tightly dedicated resources,” she said.
One caveat is that, because Continuum shifts the calculation of database costs from provisioned capacity to consumption, unexpected bursts of activity could make it harder for CIOs to forecast database costs.
CIOs will therefore need to assess their own workload patterns and test whether the higher utilization and reduced idle capacity actually translate into lower overall database costs, rather than assuming that consumption-based pricing will automatically deliver savings, Walter said.
While Continuum may simplify database management, it could also deepen dependence on CockroachDB and make workloads harder to move elsewhere, she said — with the added risk that, by coupling independent databases together onto one platform, it creates a new single point of failure.
For developers though, the shift to Continuum could reduce the time and effort required to build applications, especially agentic ones.
Development teams using Continuum can design applications without having to worry as much about the database compute and storage capacity those applications will need, when that capacity needs to scale, or the operational work required to provision and manage it, said HFS’s Chaturvedi.
But, said Walter, those advantages don’t come without challenges.
“Pooling infrastructure as Continuum does is more likely to create questions around workload isolation, performance predictability, and debugging,” she said. “Enterprise teams will want to know whether one demanding workload can affect others and whether they can trace a performance problem through the shared environment.”
Existing CockroachDB customers with large fleets of distributed transactional databases are likely to be among the earliest adopters of Continuum, Walter said.
SaaS companies, financial services firms, digital platforms and AI-native businesses could also be strong candidates, particularly where applications generate unpredictable demand and database capacity needs to scale quickly, she said.
For those enterprises, though, one of the capabilities that could make Continuum most useful for unpredictable workloads is yet to arrive. Automatic compute scaling, which will help scale compute up or down as necessary to maximize cost savings without compromising availability, is “coming soon,” the company said.