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Machine Learning · head to head

Pinecone vs Apache Spark MLlib

Pinecone logo

Pinecone

Machine Learning

Vector database for machine learning

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: Pinecone reads and writes are billed on separate meters, and reads are far more expensive, at $16 to $18 per million against $4 to $4.50 for writes on Standard; 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: Pinecone covers Vector similarity search, Apache Spark MLlib covers Classification.

Where they differ

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

Attributes where Pinecone and Apache Spark MLlib differ
AttributePineconeApache Spark MLlib
Pricing modelfreemiumopen-source
PlatformsWebLinux, macOS, Windows
Founded20191999

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 Pinecone

  • Vector similarity search
  • Metadata filtering
  • Namespace partitioning
  • Real-time updates
  • Hybrid search
  • OpenAI
  • Cohere
  • LangChain

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.

Pinecone

  • Vector database for AI/ML applicationsnot Apache Spark MLlib
  • Semantic search implementationnot Apache Spark MLlib
  • Recommendation systemsnot Apache Spark MLlib
  • RAG (Retrieval-Augmented Generation) architecturesnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Pinecone
  • Data sciencenot Pinecone
  • Distributed computingnot Pinecone

Where each one falls short

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

Pinecone

  • Reads and writes are billed on separate meters, and reads are far more expensive, at $16 to $18 per million against $4 to $4.50 for writes on Standard
  • Unit prices vary by region, so the same workload costs different amounts in different places
  • The Standard plan carries a $50 monthly minimum and Enterprise $500, charged whether or not the usage reaches it
  • Enterprise pays more per unit as well as more in minimum, at $24 to $27 per million reads against Standard's $16 to $18
  • Indexes and namespaces are capped by plan, at 5 indexes on the free tier and 20 on Standard
  • RBAC and SSO require the Standard plan

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

Pinecone

Free
  • StarterFree
    • 2GB storage
    • 2M write units/month
    • 1M read units/month
  • Builder$20/month
    • 10GB storage
    • 5M write units
    • 2M read units
  • Standard$50/month
    • Unlimited storage ($0.33/GB/month)
    • 20 indexes per project
    • 100K namespaces
  • Enterprise$500/month
    • 99.95% uptime SLA
    • BYOC (Bring Your Own Cloud) option
    • Private endpoints

Apache Spark MLlib

Free

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

Which should you pick?

Choose Pinecone if

  • You need vector similarity search.
  • You want to start without paying.
  • You also want metadata filtering.
Pinecone 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 Pinecone or Apache Spark MLlib better?
Neither clearly leads. Pinecone 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, Pinecone or Apache Spark MLlib?
Pinecone starts at Free and Apache Spark MLlib at Free.
Does Pinecone or Apache Spark MLlib run on more platforms?
Pinecone runs on Web. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Pinecone for free?
Both have a free tier, so you can try either at no cost before committing.
What is Pinecone best used for?
Pinecone is most often used for vector database for ai/ml applications, semantic search implementation, recommendation systems, rag (retrieval-augmented generation) architectures. Of those, vector database for ai/ml applications and semantic search implementation are not what Apache Spark MLlib is typically brought in for.
What can Pinecone do that Apache Spark MLlib cannot?
Pinecone covers Vector similarity search, Metadata filtering, Namespace partitioning, Real-time updates. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

Answered from the vendors’ own pages

Pinecone: Does Pinecone offer a free plan?

Yes, Pinecone's Starter tier is free and includes 2GB storage, 2M write units/month, 1M read units/month, and supports up to 2 users and 1 project.

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
Pinecone: What are Pinecone's storage costs on the Standard plan?

On the Standard plan, storage costs $0.33/GB per month. Read units cost $16-18 per million units; write units cost $4-4.50 per million units.

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
Pinecone: What support options does Pinecone provide?

Starter tier includes community Discord support. Builder tier includes free support. Standard tier support costs $29/month for Developer or $250/month for Pro. Enterprise tier includes Pro support.

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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