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Machine Learning · head to head

Langwatch vs Apache Spark MLlib

Langwatch logo

Langwatch

Machine Learning

LLM engineering platform for testing and evaluating AI agents in production

From
Free
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Machine Learning

Scalable machine learning on Apache Spark

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Langwatch free plan limited to 50k events per month, restricting larger deployments; Apache Spark MLlib apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
  • They diverge on capability: Langwatch covers Agent simulation testing, Apache Spark MLlib covers Classification.

Where they differ

Only the attributes on which Langwatch and Apache Spark MLlib actually diverge.

Attributes where Langwatch and Apache Spark MLlib differ
AttributeLangwatchApache Spark MLlib
Pricing modelTiered subscription with usage-based overage chargesopen-source
PlatformsWeb, Docker, KubernetesLinux, macOS, Windows
FoundedUnknown1999

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 Apache Spark MLlib

  • Classification
  • Regression
  • Clustering
  • Collaborative filtering
  • Feature engineering
  • Apache Spark
  • Hadoop
  • Kafka

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 Apache Spark MLlib
  • Automated test creation from product requirementsnot Apache Spark MLlib
  • LLM response quality evaluation and scoringnot Apache Spark MLlib
  • Production agent monitoring and cost trackingnot Apache Spark MLlib
  • Governance and access control for AI systemsnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Langwatch
  • Data sciencenot Langwatch
  • Distributed computingnot 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

Apache Spark MLlib

  • Apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.

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

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib review.

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.
Langwatch review

Choose Apache Spark MLlib if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want regression.
Apache Spark MLlib review

Questions people ask

Is Langwatch or Apache Spark MLlib better?
Neither clearly leads. Langwatch starts at Free and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Langwatch or Apache Spark MLlib?
Langwatch starts at Free and Apache Spark MLlib at Free.
Does Langwatch or Apache Spark MLlib run on more platforms?
Langwatch runs on Web, Docker, Kubernetes. Apache Spark MLlib runs on Linux, macOS, Windows.
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 Apache Spark MLlib is typically brought in for.
What can Langwatch do that Apache Spark MLlib cannot?
Langwatch covers Agent simulation testing, LLM evaluation, OpenTelemetry tracing, Langy AI Engineer. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

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
Apache Spark MLlib: How much does Apache Spark MLlib cost?

MLlib is completely free and open source, licensed under the Apache License Version 2.0. There are no subscription, licensing, or usage fees.

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
Apache Spark MLlib: What licensing does MLlib use?

MLlib is licensed under Apache License Version 2.0, making it freely available for all users regardless of organization size or use case.

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
Apache Spark MLlib: How do I use MLlib?

MLlib is built into Apache Spark. Download Spark, which includes MLlib as a module, and deploy on your choice of infrastructure including Hadoop, Mesos, Kubernetes, standalone, or cloud.

Source
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