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Machine Learning · head to head

Apache Spark MLlib vs Traceloop

Apache Spark MLlib logo

Apache Spark MLlib

Machine Learning

Scalable machine learning on Apache Spark

From
Free
Rated
-
Full reviewWebsite
Traceloop logo

Traceloop

Logging

LLM reliability platform with open-source observability and evaluation

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Traceloop free tier limited to 50k spans per month and 24-hour retention, restricting production use
  • They diverge on capability: Apache Spark MLlib covers Classification, Traceloop covers Open-source SDK (OpenLLMetry).

Where they differ

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

Attributes where Apache Spark MLlib and Traceloop differ
AttributeApache Spark MLlibTraceloop
Pricing modelopen-sourceFreemium with pay-as-you-go enterprise option
PlatformsLinux, macOS, WindowsCloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby
CategoryMachine LearningLogging
Founded1999Unknown

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 Apache Spark MLlib

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

Only in Traceloop

  • Open-source SDK (OpenLLMetry)
  • Multi-provider support
  • Observability platform integration
  • Framework support
  • Monitoring dashboard
  • Evaluation system
  • Deployment flexibility

What people use each for

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

Apache Spark MLlib

  • Machine learningnot Traceloop
  • Data sciencenot Traceloop
  • Distributed computingnot Traceloop

Traceloop

  • Monitoring LLM application performance in productionnot Apache Spark MLlib
  • Instrumenting LLM apps with minimal code overheadnot Apache Spark MLlib
  • Continuous evaluation and quality scoring of LLM outputsnot Apache Spark MLlib
  • Debugging LLM application issues with full trace visibilitynot Apache Spark MLlib
  • Integrating observability data into existing monitoring stacksnot Apache Spark MLlib

Where each one falls short

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

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.

Traceloop

  • Free tier limited to 50k spans per month and 24-hour retention, restricting production use
  • Company acquisition by ServiceNow creates uncertainty about future roadmap
  • Requires integration with separate observability platforms for visualization
  • Less feature-rich than dedicated LLM evaluation platforms

Pricing, plan by plan

Apache Spark MLlib

Free

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

Traceloop

Free
  • FreeFree
    • 50,000 spans per month
    • Up to 5 seats
    • 24-hour data retention
  • Enterprise$undefined/custom
    • Unlimited spans per month
    • Unlimited seats
    • Custom data retention

Which should you pick?

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

Choose Traceloop if

  • You need open-source sdk (openllmetry).
  • You want to start without paying.
  • You work on Cloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby.
  • You also want multi-provider support.
Traceloop review

Questions people ask

Is Apache Spark MLlib or Traceloop better?
Neither clearly leads. Apache Spark MLlib starts at Free and Traceloop at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Spark MLlib or Traceloop?
Apache Spark MLlib starts at Free and Traceloop at Free.
Does Apache Spark MLlib or Traceloop run on more platforms?
Apache Spark MLlib runs on Linux, macOS, Windows. Traceloop runs on Cloud, On-premises, Air-gapped, Python, TypeScript, Go, Ruby.
Can I use Apache Spark MLlib for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Spark MLlib best used for?
Apache Spark MLlib is most often used for machine learning, data science, distributed computing. Of those, machine learning and data science are not what Traceloop is typically brought in for.
What can Apache Spark MLlib do that Traceloop cannot?
Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Traceloop covers Open-source SDK (OpenLLMetry), Multi-provider support, Observability platform integration, Framework support.

Answered from the vendors’ own pages

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
Traceloop: Is OpenLLMetry open-source?

Yes, OpenLLMetry is Traceloop's open-source SDK built on OpenTelemetry standards. It allows teams to instrument LLM applications with just 2 lines of code and send data to 25+ observability platforms.

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
Traceloop: What is the impact of ServiceNow acquisition?

Traceloop is joining ServiceNow, representing a strategic acquisition that will broaden enterprise adoption and integration capabilities. Current operations continue with free and enterprise options available.

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
Traceloop: How many LLM providers and frameworks does Traceloop support?

Traceloop supports 20+ LLM providers including OpenAI and Anthropic, and integrates with frameworks like LangChain and LlamaIndex. It can send data to 25+ observability platforms.

Source
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