AI · head to head
Galileo vs Apache Spark MLlib

Galileo
AI
Evaluation and observability platform for GenAI applications and agents
- From
- Free
- Rated
- -

Apache Spark MLlib
Machine Learning
Scalable machine learning on Apache Spark
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Galileo the free plan is limited to 5,000 traces per month, which is quickly outgrown by production workloads.; 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: Galileo covers Pre-built evaluations, Apache Spark MLlib covers Classification.
Where they differ
Only the attributes on which Galileo and Apache Spark MLlib actually diverge.
| Attribute | Galileo | Apache Spark MLlib |
|---|---|---|
| Pricing model | freemium | open-source |
| Platforms | web, api | Linux, macOS, Windows |
| Category | AI | Machine Learning |
| Founded | Unknown | 1999 |
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 Galileo
- Pre-built evaluations
- Ground truth capture
- Luna models
- Agent behavior analysis
- Production guardrails
- Flexible deployment
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.
Galileo
- Evaluating RAG and agent applications before production releasenot Apache Spark MLlib
- Monitoring live GenAI applications for failures and driftnot Apache Spark MLlib
- Applying real-time guardrails without custom integration worknot Apache Spark MLlib
- Reducing evaluation costs using distilled Luna judge modelsnot Apache Spark MLlib
Apache Spark MLlib
- Machine learningnot Galileo
- Data sciencenot Galileo
- Distributed computingnot Galileo
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Galileo
- The free plan is limited to 5,000 traces per month, which is quickly outgrown by production workloads.
- Real-time guardrails and unlimited trace capacity are reserved for the custom-priced Enterprise tier.
- Pro plan pricing scales with trace volume, so costs can grow unpredictably as usage increases.
- On-premises deployment requires an Enterprise contract rather than being available self-serve.
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
Galileo
Free- FreeFree
- 5,000 traces/month
- Unlimited users
- Unlimited custom evaluations
- Pro$100/month
- 50,000 traces/month
- Standard role-based access control
- Advanced analytics and insights
- Enterprise$undefined/mo
- Unlimited trace capacity
- Custom rate limits
- Hosted, VPC, or on-prem deployment
Apache Spark MLlib
FreeNo published plan breakdown. See the Apache Spark MLlib review.
Which should you pick?
Choose Galileo if
- You need pre-built evaluations.
- You want to start without paying.
- You work on web, api.
- You also want ground truth capture.
Choose Apache Spark MLlib if
- You need classification.
- You want to start without paying.
- You work on Linux, macOS, Windows.
- You also want regression.
Questions people ask
- Is Galileo or Apache Spark MLlib better?
- Neither clearly leads. Galileo 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, Galileo or Apache Spark MLlib?
- Galileo starts at Free and Apache Spark MLlib at Free.
- Does Galileo or Apache Spark MLlib run on more platforms?
- Galileo runs on web, api. Apache Spark MLlib runs on Linux, macOS, Windows.
- Can I use Galileo for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Galileo best used for?
- Galileo is most often used for evaluating rag and agent applications before production release, monitoring live genai applications for failures and drift, applying real-time guardrails without custom integration work, reducing evaluation costs using distilled luna judge models. Of those, evaluating rag and agent applications before production release and monitoring live genai applications for failures and drift are not what Apache Spark MLlib is typically brought in for.
- What can Galileo do that Apache Spark MLlib cannot?
- Galileo covers Pre-built evaluations, Ground truth capture, Luna models, Agent behavior analysis. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.
Answered from the vendors’ own pages
Galileo: What does Galileo cost?
Galileo offers a free plan, a Pro plan at $100/month billed yearly (with a 33% annual discount), and a custom-priced Enterprise plan for unlimited trace capacity.
SourceApache 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.
SourceGalileo: Is there a free plan, and what are its limits?
The Free plan includes 5,000 traces per month with unlimited users and unlimited custom evaluations, aimed at developers and small teams experimenting with GenAI.
SourceApache 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.
SourceGalileo: How is usage metered?
Galileo's pricing scales based on the number of traces processed each month, with Free capped at 5,000, Pro at 50,000, and Enterprise offering unlimited trace capacity.
SourceApache 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.
SourceRelated pages
More on Apache Spark MLlib
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