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Machine Learning · head to head

Kubeflow vs Weaviate

Kubeflow logo

Kubeflow

Machine Learning

Machine learning toolkit for Kubernetes

From
Free
Rated
-
Full reviewWebsite
Weaviate logo

Weaviate

Machine Learning

Open-source vector database

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Kubeflow complex installation and configuration requiring Kubernetes expertise, upgrade paths between versions need manual CRD migrations; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
  • They diverge on capability: Kubeflow covers ML pipelines, Weaviate covers Vector and keyword search.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Kubeflow and Weaviate actually diverge.

Attributes where Kubeflow and Weaviate differ
AttributeKubeflowWeaviate
Pricing modelUnknownfreemium
PlatformsKubernetesLinux, Mac, Windows, Web
Founded20172019

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

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 Kubeflow

  • ML pipelines
  • Training operators
  • Model serving
  • Jupyter notebooks
  • Hyperparameter tuning
  • Kubernetes
  • TensorFlow
  • PyTorch

Only in Weaviate

  • Vector and keyword search
  • Built-in vectorizers
  • GraphQL API
  • Multi-tenancy
  • Hybrid search
  • OpenAI
  • Hugging Face
  • Cohere

Both cover

  • Linux support

What people use each for

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

Kubeflow

  • Machine learningnot Weaviate
  • Data analysisnot Weaviate
  • Model trainingnot Weaviate
  • Predictive analyticsnot Weaviate

Weaviate

  • Running a vector database for semantic and hybrid searchnot Kubeflow
  • Generating and storing embeddings alongside the objects they describenot Kubeflow

Where each one falls short

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

Kubeflow

  • Complex installation and configuration requiring Kubernetes expertise, upgrade paths between versions need manual CRD migrations
  • Resource-intensive infrastructure with minimal installs consuming significant CPU and memory
  • Limited multi-tenancy support and multi-cloud setup leaves users largely on their own
  • No native CI/CD integration, requiring custom glue code for versioning and automated deployments
  • Debugging jobs and monitoring workloads often requires dropping down into raw Kubernetes commands

Weaviate

  • The free tier caps at 100,000 objects, 1 GB of memory and a single collection
  • Billing is per million vector dimensions rather than per record, so wider embeddings cost proportionally more for the same object count
  • Premium is a prepaid contract starting at $400 a month rather than pay as you go
  • Storage rates do not fall consistently with tier, and Premium Dedicated is $0.1505 per GiB against $0.12 on the cheaper Flex plan
  • The Query Agent is metered separately, free to 1,000 requests a month and $30 a month plus overage beyond

Pricing, plan by plan

Kubeflow

Free

No published plan breakdown. See the Kubeflow review.

Weaviate

Free
  • Open SourceFree
    • Full features
    • Self-hosted
  • ServerlessFree
    • Managed service
    • Auto-scaling

Which should you pick?

Choose Kubeflow if

  • You need ml pipelines.
  • You want to start without paying.
  • You work on Kubernetes.
  • You also want training operators.
Kubeflow review

Choose Weaviate if

  • You need vector and keyword search.
  • You want to start without paying.
  • You work on Linux, Mac, Windows, Web.
  • You also want built-in vectorizers.
Weaviate review

Questions people ask

Is Kubeflow or Weaviate better?
Neither clearly leads. Kubeflow starts at Free and Weaviate at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Kubeflow or Weaviate?
Kubeflow starts at Free and Weaviate at Free.
Does Kubeflow or Weaviate run on more platforms?
Kubeflow runs on Kubernetes. Weaviate runs on Linux, Mac, Windows, Web.
Can I use Kubeflow for free?
Both have a free tier, so you can try either at no cost before committing.
What is Kubeflow best used for?
Kubeflow is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Weaviate is typically brought in for.
What can Kubeflow do that Weaviate cannot?
Kubeflow covers ML pipelines, Training operators, Model serving, Jupyter notebooks. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy. Both handle Linux support.

Answered from the vendors’ own pages

Kubeflow: Is Kubeflow free to use?

Yes, Kubeflow is free and open-source under Apache License 2.0. However, you pay for the underlying Kubernetes infrastructure, which typically costs $500 to $5,000 per month depending on scale and cloud provider.

Source
Weaviate: What pricing options does Weaviate offer?

Weaviate provides a free tier with usage-based pricing, plus enterprise options. Visit the pricing page for detailed information on plans.

Source
Kubeflow: Do I need Kubernetes expertise to use Kubeflow?

Kubeflow requires significant Kubernetes and DevOps expertise. The installation deploys dozens of services and CRDs, often requiring manual configuration and troubleshooting. Data scientists typically need to convert scripts to containerized components.

Source
Weaviate: Does Weaviate offer customer support?

Yes, support is included with Weaviate's cloud offerings. Enterprise customers receive first-class support from their global team of experts.

Source
Kubeflow: What platforms can Kubeflow run on?

Kubeflow runs on any Kubernetes-compliant cluster, including on-premise, AWS, Azure, Google Cloud, and hybrid environments. This multi-cloud portability is one of its key advantages over managed alternatives.

Source
Weaviate: Can I deploy Weaviate on my own infrastructure?

Yes. Weaviate is open source and deployment-agnostic. You can run it in your own cloud environment or use their managed cloud service.

Source
Kubeflow: How does Kubeflow compare to managed services like SageMaker?

Kubeflow offers multi-cloud portability and lower long-term costs but requires more operational overhead. SageMaker provides a fully managed experience with better UI and less infrastructure work, but creates vendor lock-in to AWS.

Source
Weaviate: What data security features does Weaviate provide?

Weaviate includes security & governance, RBAC, SOC 2 and HIPAA compliance, along with multi-tenancy and high availability for enterprise requirements.

Source
Weaviate: How do I get started with Weaviate?

Sign up for their cloud tier, create your first dataset, connect an LLM, and build your AI app. Documentation and quickstart guides are available for Python, Go, TypeScript, and JavaScript.

Source
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