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Machine Learning · head to head

Langwatch vs Weaviate

Langwatch logo

Langwatch

Machine Learning

LLM engineering platform for testing and evaluating AI agents in production

From
Free
Rated
-
Weaviate logo

Weaviate

Machine Learning

Open-source vector database

From
Free
Rated
-

The short version

  • Each has a real cost: Langwatch free plan limited to 50k events per month, restricting larger deployments; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
  • They diverge on capability: Langwatch covers Agent simulation testing, Weaviate covers Vector and keyword search.

Where they differ

Only the attributes on which Langwatch and Weaviate actually diverge.

Attributes where Langwatch and Weaviate differ
AttributeLangwatchWeaviate
Pricing modelTiered subscription with usage-based overage chargesfreemium
PlatformsWeb, Docker, KubernetesLinux, Mac, Windows, Web
FoundedUnknown2019

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 Langwatch

  • Agent simulation testing
  • LLM evaluation
  • OpenTelemetry tracing
  • Langy AI Engineer
  • Governance controls
  • Multiple deployment options
  • Framework 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.

Langwatch

  • Continuous testing of AI agents before production deploymentnot Weaviate
  • Automated test creation from product requirementsnot Weaviate
  • LLM response quality evaluation and scoringnot Weaviate
  • Production agent monitoring and cost trackingnot Weaviate
  • Governance and access control for AI systemsnot Weaviate

Weaviate

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

Where each one falls short

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

Langwatch

  • Free plan limited to 50k events per month, restricting larger deployments
  • Pricing in EUR may complicate budgeting for US-based teams
  • Usage-based overage model can create unpredictable costs
  • Self-hosted option requires DevOps expertise

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

Langwatch

Free
  • DeveloperFree
    • 50k events per month
    • 14-day data access
    • 2 users
  • Growth$29/month
    • 200k events per month included
    • 5 EUR per 100k additional events
    • 30-day data retention
  • Enterprise$undefined/custom
    • Custom event limits
    • Hybrid, self-hosted or on-premises deployment
    • Custom SSO and RBAC

Weaviate

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

Which should you pick?

Choose Langwatch if

  • You need agent simulation testing.
  • You want to start without paying.
  • You work on Web, Docker, Kubernetes.
  • You also want llm evaluation.

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 Langwatch or Weaviate better?
Neither clearly leads. Langwatch 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, Langwatch or Weaviate?
Langwatch starts at Free and Weaviate at Free.
Does Langwatch or Weaviate run on more platforms?
Langwatch runs on Web, Docker, Kubernetes. Weaviate runs on Linux, Mac, Windows, Web.
Can I use Langwatch for free?
Both have a free tier, so you can try either at no cost before committing.
What is Langwatch best used for?
Langwatch is most often used for continuous testing of ai agents before production deployment, automated test creation from product requirements, llm response quality evaluation and scoring, production agent monitoring and cost tracking. Of those, continuous testing of ai agents before production deployment and automated test creation from product requirements are not what Weaviate is typically brought in for.
What can Langwatch do that Weaviate cannot?
Langwatch covers Agent simulation testing, LLM evaluation, OpenTelemetry tracing, Langy AI Engineer. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy.

Answered from the vendors’ own pages

Langwatch: Is there a permanent free tier?

Yes, Langwatch's Developer plan is free forever with 50k events per month, 14-day data access, 2 users, and no credit card required. It is specifically designed for individual developers prototyping AI applications.

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
Langwatch: What is Langy and how does it save time?

Langy is an AI-powered tool that automates test creation. It converts product requirements into test scenarios, runs simulations, scores results, and generates pull requests with fixes in a median of 14 minutes.

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
Langwatch: What frameworks does Langwatch support?

Langwatch works with LangGraph, LangChain, CrewAI, OpenAI Agents, AWS Bedrock, Azure OpenAI, Vertex AI, and other major LLM frameworks and platforms.

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
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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