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Cloud · head to head

Cerebrium vs OpenEBS

Cerebrium logo

Cerebrium

Cloud

Serverless GPU infrastructure for real-time AI inference and applications

From
Free
Rated
-
Full reviewWebsite
OpenEBS logo

OpenEBS

Cloud

Open source container-attached storage for Kubernetes

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Cerebrium free Hobby tier limited to 3 apps and 5 GPU concurrency; OpenEBS there is no vendor on the other end of an incident unless you separately contract DataCore, so an outage at three in the morning is resolved by your own team and a public Slack channel.
  • They diverge on capability: Cerebrium covers Ultra-fast cold starts, OpenEBS covers Replicated engine.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Cerebrium and OpenEBS actually diverge.

Attributes where Cerebrium and OpenEBS differ
AttributeCerebriumOpenEBS
Pricing modelFreemium with monthly plans and per-second compute chargesOpen source, no licence fee
PlatformsCloud, DockerLinux

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Cloud).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Cerebrium

  • Ultra-fast cold starts
  • Elastic scaling
  • Bring your own code
  • Multi-region failover
  • WebSocket and streaming
  • Asynchronous jobs
  • CI/CD with gradual rollouts
  • OpenTelemetry integration

Only in OpenEBS

  • Replicated engine
  • Local PV engines
  • Kubernetes-native management
  • Snapshots and clones
  • No licence fee
  • Hardware independence

What people use each for

The jobs each tool is most often brought in to do.

Cerebrium

  • Deploying voice agents and conversational AI applicationsnot OpenEBS
  • Video and image model serving with low latencynot OpenEBS
  • LLM inference and completion endpointsnot OpenEBS
  • Real-time embeddings and vector database operationsnot OpenEBS
  • Distributed model training with hyperparameter sweepsnot OpenEBS

OpenEBS

  • Running Cassandra or Kafka on Kubernetes where the application already replicates and node-local volumes are sufficientnot Cerebrium
  • A platform team that needs persistent volumes on bare metal Kubernetes without a per node subscriptionnot Cerebrium
  • An edge or lab deployment where a commercial storage licence cannot be justifiednot Cerebrium
  • Replacing hostpath volumes with something that has snapshots and a Container Storage Interface drivernot Cerebrium

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Cerebrium

  • Free Hobby tier limited to 3 apps and 5 GPU concurrency
  • Standard plan at $100/month required for production deployments
  • Per-second compute pricing requires continuous cost monitoring
  • Storage costs add up for large model files

OpenEBS

  • There is no vendor on the other end of an incident unless you separately contract DataCore, so an outage at three in the morning is resolved by your own team and a public Slack channel.
  • The project has several storage engines with different maturity and different operational characteristics, and choosing the wrong one for your workload produces poor results that look like a product failure.
  • Documentation and upgrade guidance assume real Kubernetes storage knowledge, so teams without that expertise underestimate the operational load they are taking on.
  • Project governance shifted after DataCore acquired MayaData in 2021, which means the direction of a supposedly neutral project is influenced by one commercial sponsor.
  • Disaster recovery, cross-cluster replication and policy-driven data services are thinner than in the commercial alternatives, so organisations with those requirements end up building them or buying a product anyway.

Pricing, plan by plan

Cerebrium

Free
  • HobbyFree
    • 3 user seats
    • Up to 3 deployed apps
    • 5 GPU concurrency
  • Standard$100/month
    • Unlimited seats and apps
    • 30 GPU concurrency
    • Custom domains
  • Enterprise$undefined/custom
    • Unlimited resources
    • Volume discounts
    • Dedicated support
  • GPU Compute$undefined/per-second
    • T4: $0.000164/s
    • H100: $0.00167/s

OpenEBS

Free
  • OpenEBSFree
    • Apache 2.0 licensed
    • All storage engines included
    • No node or capacity limits

Which should you pick?

Choose Cerebrium if

  • You need ultra-fast cold starts.
  • You want to start without paying.
  • You work on Cloud, Docker.
  • You also want elastic scaling.
Cerebrium review

Choose OpenEBS if

  • You need replicated engine.
  • You want to start without paying.
  • You work on Linux.
  • You also want local pv engines.
OpenEBS review

Questions people ask

Is Cerebrium or OpenEBS better?
Neither clearly leads. Cerebrium starts at Free and OpenEBS at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cerebrium or OpenEBS?
Cerebrium starts at Free and OpenEBS at Free.
Does Cerebrium or OpenEBS run on more platforms?
Cerebrium runs on Cloud, Docker. OpenEBS runs on Linux.
Can I use Cerebrium for free?
Both have a free tier, so you can try either at no cost before committing.
What is Cerebrium best used for?
Cerebrium is most often used for deploying voice agents and conversational ai applications, video and image model serving with low latency, llm inference and completion endpoints, real-time embeddings and vector database operations. Of those, deploying voice agents and conversational ai applications and video and image model serving with low latency are not what OpenEBS is typically brought in for.
What can Cerebrium do that OpenEBS cannot?
Cerebrium covers Ultra-fast cold starts, Elastic scaling, Bring your own code, Multi-region failover. OpenEBS covers Replicated engine, Local PV engines, Kubernetes-native management, Snapshots and clones.

Answered from the vendors’ own pages

Cerebrium: Is Cerebrium only for inference or can it train models?

Cerebrium supports both inference serving and model training with hyperparameter sweeps. It enables deployment of voice agents, LLMs, video models, and other AI applications.

Source
OpenEBS: Who supports it in production?

The project is community supported. Commercial support is available from DataCore, which acquired the original sponsor MayaData in 2021. Establish that relationship before production, not during an incident.

Cerebrium: How do the cold starts compare to other platforms?

Cerebrium achieves 2-4 second cold starts through memory and GPU snapshotting, significantly faster than traditional 30+ second cold boots. This is competitive with platforms like Beam Cloud.

Source
OpenEBS: Which engine should we use?

If your application replicates its own data, use a Local engine and avoid replicating twice. If it does not, such as with PostgreSQL, use the Replicated engine.

Cerebrium: What compliance certifications does Cerebrium have?

Cerebrium maintains SOC 2 Type II compliance, HIPAA certification, GDPR compliance, and ISO certification. It provides gVisor container isolation and configurable data residency for regulated workloads.

Source
OpenEBS: Does it cost anything?

No licence fee. The cost is operational, and a support contract if you want someone accountable.

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