Machine Learning & Data Science · head to head
Seldon vs BigQuery ML
Seldon
Machine Learning & Data Science
Deploy, scale, and monitor machine learning models
- From
- Free
- Rated
- -
BigQuery ML
Machine Learning & Data Science
Machine learning in BigQuery using SQL
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Seldon production deployment requires a Kubernetes cluster, whether managed such as GKE, EKS or AKS, or on-premises such as OpenShift; BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- They diverge on capability: Seldon covers Model serving, BigQuery ML covers SQL-based ML.
Where they differ
Only the attributes on which Seldon and BigQuery ML actually diverge.
| Attribute | Seldon | BigQuery ML |
|---|---|---|
| Pricing model | freemium | usage-based |
| Platforms | Linux | Web |
| Founded | 2014 | 2008 |
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 Seldon
- Model serving
- A/B testing
- Canary deployments
- Outlier detection
- Model explainability
- Kubernetes
- Istio
- Prometheus
Only in BigQuery ML
- SQL-based ML
- AutoML Tables
- Model export
- Prediction functions
- Feature preprocessing
- BigQuery
- Vertex AI
- TensorFlow
What people use each for
The jobs each tool is most often brought in to do.
Seldon
- Serving and routing machine learning models on Kubernetesnot BigQuery ML
- Building multi-step inference pipelines with A/B tests and explainersnot BigQuery ML
BigQuery ML
- Training models in SQL without exporting datanot Seldon
- Linear and logistic regression on warehouse datanot Seldon
- K-means clustering and matrix factorisation for recommendationsnot Seldon
- Time series forecasting with ARIMA_PLUSnot Seldon
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Seldon
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Seldon
- Production deployment requires a Kubernetes cluster, whether managed such as GKE, EKS or AKS, or on-premises such as OpenShift
- The documented components carry both minimum and maximum supported versions, so newer Kubernetes and dependency versions are not automatically supported
- Dataflow Pipelines need an additional component that the docs recommend avoiding installing when pipelines are not used
- The Docker Compose install is offered as a lightweight alternative for environments without Kubernetes rather than as a production path
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
Pricing, plan by plan
Seldon
Free- Seldon CoreFree
- Open source
- Kubernetes deployment
- Model serving
- Seldon DeployFree
- Enterprise features
- GUI
- Monitoring
BigQuery ML
Free- Free TierFree
- 10GB storage
- 1TB queries
- On-Demand$5/TB
- Pay per TB scanned
- ML training costs
Which should you pick?
Choose Seldon if
- You need model serving.
- You want to start without paying.
- You work on Linux.
- You also want a/b testing.
Choose BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Questions people ask
- Is Seldon or BigQuery ML better?
- Neither clearly leads. Seldon starts at Free and BigQuery ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Seldon or BigQuery ML?
- Seldon starts at Free and BigQuery ML at Free.
- Does Seldon or BigQuery ML run on more platforms?
- Seldon runs on Linux. BigQuery ML runs on Web.
- Can I use Seldon for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Seldon best used for?
- Seldon is most often used for serving and routing machine learning models on kubernetes, building multi-step inference pipelines with a/b tests and explainers. Of those, serving and routing machine learning models on kubernetes and building multi-step inference pipelines with a/b tests and explainers are not what BigQuery ML is typically brought in for.
- What can Seldon do that BigQuery ML cannot?
- Seldon covers Model serving, A/B testing, Canary deployments, Outlier detection. BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions.