Machine Learning & Data Science · head to head
BigQuery ML vs Milvus
BigQuery ML
Machine Learning & Data Science
Machine learning in BigQuery using SQL
- From
- Free
- Rated
- -
Milvus
Machine Learning & Data Science
Open-source vector database for scalable similarity search
- From
- Free
- Rated
- -
The short version
- Each has a real cost: BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it; Milvus vector dimensions are capped at 32,768
- They diverge on capability: BigQuery ML covers SQL-based ML, Milvus covers Billion-scale vectors.
Where they differ
Only the attributes on which BigQuery ML and Milvus actually diverge.
| Attribute | BigQuery ML | Milvus |
|---|---|---|
| Pricing model | usage-based | freemium |
| Platforms | Web | Linux, Mac, Windows, Web |
| Founded | 2008 | 2017 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning & Data Science).
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
- Cloud Storage
Only in Milvus
- Billion-scale vectors
- Multiple index types
- GPU acceleration
- Hybrid search
- Data partitioning
- PyTorch
- Hugging Face
- LangChain
Both cover
- TensorFlow
- 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 Milvus
- Linear and logistic regression on warehouse datanot Milvus
- K-means clustering and matrix factorisation for recommendationsnot Milvus
- Time series forecasting with ARIMA_PLUSnot Milvus
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Milvus
Milvus
- Self hosting a vector database for semantic searchnot BigQuery ML
- Storing and querying embeddings for retrieval augmented generationnot BigQuery ML
- Similarity search over images, audio or text at scalenot 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
Milvus
- Vector dimensions are capped at 32,768
- A collection is limited to 64 fields, 1,024 partitions and 16 shards
- Only 1 index is allowed per field
- Search returns at most 16,384 vectors as top-k, and nq is capped at 16,384
- Input and output per RPC is capped at 64 MB for insert, search and query
- VARCHAR values are limited to 65,535 characters
- Data loaded into query nodes cannot exceed 90% of available memory
- An instance supports at most 65,536 collections
Pricing, plan by plan
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Milvus
Free- Open SourceFree
- Full features
- Self-hosted
- Community support
- Zilliz CloudFree
- Managed service
- Free tier available
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 Milvus if
- You need billion-scale vectors.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want multiple index types.
Questions people ask
- Is BigQuery ML or Milvus better?
- Neither clearly leads. BigQuery ML starts at Free and Milvus at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, BigQuery ML or Milvus?
- BigQuery ML starts at Free and Milvus at Free.
- Does BigQuery ML or Milvus run on more platforms?
- BigQuery ML runs on Web. Milvus runs on Linux, Mac, Windows, Web.
- 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 Milvus is typically brought in for.
- What can BigQuery ML do that Milvus cannot?
- BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions. Milvus covers Billion-scale vectors, Multiple index types, GPU acceleration, Hybrid search. Both handle TensorFlow, Web support.
Related pages
More on BigQuery ML
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