Machine Learning · head to head
Dataiku vs Pinecone
The short version
- Each has a real cost: Dataiku no pricing is published at any tier, and the plans page carries no figures at all; 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
- They diverge on capability: Dataiku covers Visual data prep, Pinecone covers Vector similarity search.
Where they differ
Only the attributes on which Dataiku and Pinecone actually diverge.
Identical on both: starting price (Free), pricing model (freemium), 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 Dataiku
- Visual data prep
- AutoML
- MLOps
- Collaboration
- Governence
- Python
- R
- Spark
Only in Pinecone
- Vector similarity search
- Metadata filtering
- Namespace partitioning
- Real-time updates
- Hybrid search
- OpenAI
- Cohere
- LangChain
Both cover
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Dataiku
- Building and deploying data science and machine learning pipelinesnot Pinecone
- Giving analysts and data scientists a shared visual and code environmentnot Pinecone
Pinecone
- Vector database for AI/ML applicationsnot Dataiku
- Semantic search implementationnot Dataiku
- Recommendation systemsnot Dataiku
- RAG (Retrieval-Augmented Generation) architecturesnot Dataiku
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Dataiku
- No pricing is published at any tier, and the plans page carries no figures at all
- User, row and compute limits are not stated, so nothing about scale can be assessed before contacting sales
- Access begins with a demo request or a trial rather than a self serve signup
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
Pricing, plan by plan
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
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
Which should you pick?
Choose Dataiku if
- You need visual data prep.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want automl.
Choose Pinecone if
- You need vector similarity search.
- You want to start without paying.
- You also want metadata filtering.
Questions people ask
- Is Dataiku or Pinecone better?
- Neither clearly leads. Dataiku starts at Free and Pinecone at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Dataiku or Pinecone?
- Dataiku starts at Free and Pinecone at Free.
- Does Dataiku or Pinecone run on more platforms?
- Dataiku runs on Linux, Mac, Windows, Web. Pinecone runs on Web.
- Can I use Dataiku for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Dataiku best used for?
- Dataiku is most often used for building and deploying data science and machine learning pipelines, giving analysts and data scientists a shared visual and code environment. Of those, building and deploying data science and machine learning pipelines and giving analysts and data scientists a shared visual and code environment are not what Pinecone is typically brought in for.
- What can Dataiku do that Pinecone cannot?
- Dataiku covers Visual data prep, AutoML, MLOps, Collaboration. Pinecone covers Vector similarity search, Metadata filtering, Namespace partitioning, Real-time updates. Both handle Web support.
Answered from the vendors’ own pages
Dataiku: What are Dataiku pricing tiers and costs?
Dataiku pricing information is not available on their public website. Customers must contact Dataiku sales directly to request pricing, trial access, and licensing information.
SourcePinecone: 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.
SourceDataiku: Does Dataiku offer a free tier or trial?
Free tier or trial availability for Dataiku cannot be determined from publicly accessible pages. Contact Dataiku directly to inquire about evaluation options.
SourcePinecone: 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.
SourcePinecone: 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.
SourceRelated pages
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- Pinecone vs TensorFlow
- Pinecone vs Comet ML
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- Pinecone vs Python
- Pinecone vs PyTorch
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- Pinecone vs Weaviate
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- Pinecone vs Alteryx
- Pinecone vs Anaconda


