Machine Learning · head to head
BigQuery ML vs Pinecone
The short version
- Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; 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: BigQuery ML covers SQL-based ML, Pinecone covers Vector similarity search.
Where they differ
Only the attributes on which BigQuery ML and Pinecone actually diverge.
| Attribute | BigQuery ML | Pinecone |
|---|---|---|
| Pricing model | usage-based | freemium |
| Founded | 2008 | 2019 |
Identical on both: starting price (Free), free tier (Yes), platforms (Web), 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 BigQuery ML
- SQL-based ML
- AutoML Tables
- Model export
- Prediction functions
- Feature preprocessing
- BigQuery
- Vertex AI
- TensorFlow
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.
BigQuery ML
- Training models in SQL without exporting datanot Pinecone
- Linear and logistic regression on warehouse datanot Pinecone
- K-means clustering and matrix factorisation for recommendationsnot Pinecone
- Time series forecasting with ARIMA_PLUSnot Pinecone
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Pinecone
Pinecone
- Vector database for AI/ML applicationsnot BigQuery ML
- Semantic search implementationnot BigQuery ML
- Recommendation systemsnot BigQuery ML
- RAG (Retrieval-Augmented Generation) architecturesnot BigQuery ML
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
BigQuery ML
- Not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- Billed through BigQuery compute and storage rather than as its own product, so training cost tracks data scanned
- Remote models incur extra Agent Platform charges on top
- Externally trained model types such as boosted trees and AutoML run through Agent Platform rather than inside BigQuery
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
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
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 BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Choose Pinecone if
- You need vector similarity search.
- You want to start without paying.
- You also want metadata filtering.
Questions people ask
- Is BigQuery ML or Pinecone better?
- Neither clearly leads. BigQuery ML 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, BigQuery ML or Pinecone?
- BigQuery ML starts at Free and Pinecone at Free.
- Does BigQuery ML or Pinecone run on more platforms?
- Both run on Web, so platform support will not decide this one for you.
- Can I use BigQuery ML for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is BigQuery ML best used for?
- BigQuery ML is most often used for training models in sql without exporting data, linear and logistic regression on warehouse data, k-means clustering and matrix factorisation for recommendations, time series forecasting with arima_plus. Of those, training models in sql without exporting data and linear and logistic regression on warehouse data are not what Pinecone is typically brought in for.
- What can BigQuery ML do that Pinecone cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Pinecone covers Vector similarity search, Metadata filtering, Namespace partitioning, Real-time updates. Both handle Web support.
Answered from the vendors’ own pages
BigQuery ML: How much does Google Cloud BigQuery ML cost?
BigQuery ML pricing is not specified separately on Google Cloud's pricing page. It follows the same pay-as-you-go model as BigQuery, charging per terabyte of data scanned during analysis. Customers receive $300 in free credits and can use 20+ products free up to monthly limits.
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.
SourceBigQuery ML: Does Google Cloud offer a free trial?
Yes, new customers get $300 in free credits and all customers can use 20+ Google Cloud products free up to their monthly usage limits.
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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