AI · head to head
LangGraph vs Weaviate
The short version
- Each has a real cost: LangGraph steeper learning curve compared to high-level abstractions; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
- They diverge on capability: LangGraph covers Human-in-the-loop controls, Weaviate covers Vector and keyword search.
Where they differ
Only the attributes on which LangGraph and Weaviate actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
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 LangGraph
- Human-in-the-loop controls
- Customizable workflows
- Memory management
- Token-by-token streaming
- Low-level control
- Multi-agent support
Only in Weaviate
- Vector and keyword search
- Built-in vectorizers
- GraphQL API
- Multi-tenancy
- Hybrid search
- OpenAI
- Hugging Face
- Cohere
What people use each for
The jobs each tool is most often brought in to do.
LangGraph
- Building production AI agents with auditable workflowsnot Weaviate
- Designing multi-agent systems for complex tasksnot Weaviate
- Implementing human oversight in autonomous systemsnot Weaviate
- Creating reliable agentic applications at scalenot Weaviate
Weaviate
- Running a vector database for semantic and hybrid searchnot LangGraph
- Generating and storing embeddings alongside the objects they describenot LangGraph
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
LangGraph
- Steeper learning curve compared to high-level abstractions
- Requires understanding of graph-based architecture
- Debugging complex workflows can be challenging
- Not optimized for simple, one-off use cases
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
LangGraph
Free- Open SourceFree
- MIT-licensed framework
- Self-hosted deployment
- Full API access
- LangGraph Platform$35/month
- Managed hosting
- Enterprise deployment
- Integrated tooling
Weaviate
Free- Open SourceFree
- Full features
- Self-hosted
- ServerlessFree
- Managed service
- Auto-scaling
Which should you pick?
Choose LangGraph if
- You need human-in-the-loop controls.
- You want to start without paying.
- You work on Python, JavaScript, Web.
- You also want customizable workflows.
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.
Questions people ask
- Is LangGraph or Weaviate better?
- Neither clearly leads. LangGraph 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, LangGraph or Weaviate?
- LangGraph starts at Free and Weaviate at Free.
- Does LangGraph or Weaviate run on more platforms?
- LangGraph runs on Python, JavaScript, Web. Weaviate runs on Linux, Mac, Windows, Web.
- Can I use LangGraph for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is LangGraph best used for?
- LangGraph is most often used for building production ai agents with auditable workflows, designing multi-agent systems for complex tasks, implementing human oversight in autonomous systems, creating reliable agentic applications at scale. Of those, building production ai agents with auditable workflows and designing multi-agent systems for complex tasks are not what Weaviate is typically brought in for.
- What can LangGraph do that Weaviate cannot?
- LangGraph covers Human-in-the-loop controls, Customizable workflows, Memory management, Token-by-token streaming. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy.
Answered from the vendors’ own pages
LangGraph: Is LangGraph free to use?
Yes. The core LangGraph framework is MIT-licensed and completely free. You only pay if you use the optional managed LangGraph Platform for hosting.
SourceWeaviate: 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.
SourceLangGraph: What programming languages does LangGraph support?
LangGraph provides first-class support for Python and JavaScript, enabling cross-platform agent development.
SourceWeaviate: 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.
SourceLangGraph: Can I deploy LangGraph in production?
Yes. LangGraph can be self-hosted on your own infrastructure or deployed through LangGraph Platform with enterprise support and SLA guarantees.
SourceWeaviate: 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.
SourceWeaviate: 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.
SourceWeaviate: 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.
SourceRelated pages
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