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Apache Spark MLlib vs Weaviate

Apache Spark MLlib logo

Apache Spark MLlib

Software

Scalable machine learning on Apache Spark

From
Free
Rated
-
Full reviewWebsite
Weaviate logo

Weaviate

Software

Open-source vector database

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.; Weaviate the free tier caps at 100,000 objects, 1 GB of memory and a single collection
  • They diverge on capability: Apache Spark MLlib covers Classification, Weaviate covers Vector and keyword search.

Where they differ

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

Attributes where Apache Spark MLlib and Weaviate differ
AttributeApache Spark MLlibWeaviate
Pricing modelopen-sourcefreemium
PlatformsLinux, macOS, WindowsLinux, Mac, Windows, Web
Founded19992019

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 Apache Spark MLlib

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

Only in Weaviate

  • Vector and keyword search
  • Built-in vectorizers
  • GraphQL API
  • Multi-tenancy
  • Hybrid search
  • OpenAI
  • Hugging Face
  • Cohere

Both cover

  • Linux support
  • Mac support
  • Windows support

What people use each for

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

Apache Spark MLlib

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

Weaviate

  • Running a vector database for semantic and hybrid searchnot Apache Spark MLlib
  • Generating and storing embeddings alongside the objects they describenot 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.

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

Apache Spark MLlib

Free

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

Weaviate

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

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 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.
Weaviate review

Questions people ask

Is Apache Spark MLlib or Weaviate better?
Neither clearly leads. Apache Spark MLlib 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, Apache Spark MLlib or Weaviate?
Apache Spark MLlib starts at Free and Weaviate at Free.
Does Apache Spark MLlib or Weaviate run on more platforms?
Apache Spark MLlib runs on Linux, macOS, Windows. Weaviate runs on Linux, Mac, Windows, Web.
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 large-scale distributed machine learning on spark clusters, classification and regression with decision trees, random forests, gradient-boosted trees, clustering with k-means and gaussian mixture models. Of those, large-scale distributed machine learning on spark clusters and classification and regression with decision trees, random forests, gradient-boosted trees are not what Weaviate is typically brought in for.
What can Apache Spark MLlib do that Weaviate cannot?
Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering. Weaviate covers Vector and keyword search, Built-in vectorizers, GraphQL API, Multi-tenancy. Both handle Linux support, Mac support, Windows support.
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