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LangChain vs Apache Spark MLlib

LangChain logo

LangChain

Software

Build applications with LLMs through composability

From
Free
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Software

Scalable machine learning on Apache Spark

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: LangChain the free Developer plan of LangSmith is limited to 1 seat; 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: LangChain covers Chains and agents, Apache Spark MLlib covers Classification.

Where they differ

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

Attributes where LangChain and Apache Spark MLlib differ
AttributeLangChainApache Spark MLlib
Pricing modelfreemiumopen-source
PlatformsLinux, Mac, WindowsLinux, macOS, Windows
Founded20221999

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

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 LangChain

  • Chains and agents
  • Retrieval-augmented generation
  • Memory management
  • Tool integration
  • Prompt templates
  • OpenAI
  • Anthropic
  • Hugging Face

Only in Apache Spark MLlib

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

Both cover

  • Linux support
  • Mac support
  • Windows support

What people use each for

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

LangChain

  • Building LLM applications and agents in Python or JavaScriptnot Apache Spark MLlib
  • Tracing and debugging LLM chains and agent runsnot Apache Spark MLlib
  • Evaluating prompt and model changes against datasetsnot Apache Spark MLlib

Apache Spark MLlib

  • Large-scale distributed machine learning on Spark clustersnot LangChain
  • Classification and regression with decision trees, random forests, gradient-boosted treesnot LangChain
  • Clustering with K-means and Gaussian Mixture Modelsnot LangChain

Where each one falls short

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

LangChain

  • The free Developer plan of LangSmith is limited to 1 seat
  • Base traces are retained for 14 days only; 400 day retention costs extra
  • Included traces are capped at 5,000 per month on Developer and 10,000 per month on Plus, with everything beyond billed pay as you go
  • Self hosted and hybrid deployment of LangSmith is Enterprise only
  • Custom SSO, RBAC and ABAC are Enterprise only
  • A support SLA is Enterprise only
  • Enterprise pricing is by quote with no published rate

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

LangChain

Free
  • Open SourceFree
    • Full framework
    • Community support
  • LangSmith$39/month
    • Debugging
    • Monitoring
    • Testing

Apache Spark MLlib

Free

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

Which should you pick?

Choose LangChain if

  • You need chains and agents.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want retrieval-augmented generation.
LangChain 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 LangChain or Apache Spark MLlib better?
Neither clearly leads. LangChain 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, LangChain or Apache Spark MLlib?
LangChain starts at Free and Apache Spark MLlib at Free.
Does LangChain or Apache Spark MLlib run on more platforms?
LangChain runs on Linux, Mac, Windows. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use LangChain for free?
Both have a free tier, so you can try either at no cost before committing.
What is LangChain best used for?
LangChain is most often used for building llm applications and agents in python or javascript, tracing and debugging llm chains and agent runs, evaluating prompt and model changes against datasets. Of those, building llm applications and agents in python or javascript and tracing and debugging llm chains and agent runs are not what Apache Spark MLlib is typically brought in for.
What can LangChain do that Apache Spark MLlib cannot?
LangChain covers Chains and agents, Retrieval-augmented generation, Memory management, Tool integration. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Both handle Linux support, Mac support, Windows support.
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