AI · head to head
Arize AI vs BigQuery ML

Arize AI
AI
AI engineering platform for observability and evaluation of agents and LLM apps
- From
- Free
- Free plan
- Yes

BigQuery ML
Machine Learning
Machine learning in BigQuery using SQL
- From
- Free
- Free plan
- Yes
The short version
- Each has a real cost: Arize AI the free plan caps trace spans at 25,000 per month with only 15 days of retention.; BigQuery ML not available in BigQuery's Standard edition, so the cheapest tier cannot use it
- They diverge on capability: Arize AI covers End-to-end tracing, BigQuery ML covers SQL-based ML.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Arize AI and BigQuery ML actually diverge.
| Attribute | Arize AI | BigQuery ML |
|---|---|---|
| Pricing model | freemium | usage-based |
| Platforms | web, api | Web |
| Category | AI | Machine Learning |
| Founded | Unknown | 2008 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
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 Arize AI
- End-to-end tracing
- Evaluation framework
- Prompt testing and improvement
- Alyx AI engineering agent
- Custom dashboards
- Data warehouse integrations
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.
Arize AI
- Tracing and debugging production AI agentsnot BigQuery ML
- Running large-scale evaluations across traces and sessionsnot BigQuery ML
- Improving prompts before production rolloutnot BigQuery ML
- Storing and querying GenAI traces alongside a data warehousenot BigQuery ML
BigQuery ML
- Training models in SQL without exporting datanot Arize AI
- Linear and logistic regression on warehouse datanot Arize AI
- K-means clustering and matrix factorisation for recommendationsnot Arize AI
- Time series forecasting with ARIMA_PLUSnot Arize AI
- Running imported ONNX, TensorFlow or XGBoost models against BigQuery datanot Arize AI
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Arize AI
- The free plan caps trace spans at 25,000 per month with only 15 days of retention.
- Self-hosted deployment and Data Fabric integration are restricted to the custom-priced Enterprise tier.
- Pricing beyond the $50/month Pro plan requires a custom quote, making cost planning less transparent at scale.
- Advanced compliance features like HIPAA are only available on Enterprise.
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
Arize AI
Free- AX FreeFree
- 25k trace spans/month
- 1 GB storage/month
- 15-day retention
- AX Pro$50/month
- 50k trace spans/month
- 10 GB storage/month
- 30-day retention
- AX Enterprise$undefined/mo
- Custom trace spans, storage, and retention
- SaaS or self-hosted deployment
- Managed agents and Data Fabric
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 Arize AI if
- You need end-to-end tracing.
- You want to start without paying.
- You work on web, api.
- You also want evaluation framework.
Choose BigQuery ML if
- You need sql-based ml.
- You want to start without paying.
- You also want automl tables.
Questions people ask
- Is Arize AI or BigQuery ML better?
- Neither clearly leads. Arize AI 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, Arize AI or BigQuery ML?
- Arize AI starts at Free and BigQuery ML at Free.
- Does Arize AI or BigQuery ML run on more platforms?
- Arize AI runs on web, api. BigQuery ML runs on Web.
- Can I use Arize AI for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Arize AI best used for?
- Arize AI is most often used for tracing and debugging production ai agents, running large-scale evaluations across traces and sessions, improving prompts before production rollout, storing and querying genai traces alongside a data warehouse. Of those, tracing and debugging production ai agents and running large-scale evaluations across traces and sessions are not what BigQuery ML is typically brought in for.
- What can Arize AI do that BigQuery ML cannot?
- Arize AI covers End-to-end tracing, Evaluation framework, Prompt testing and improvement, Alyx AI engineering agent. BigQuery ML covers SQL-based ML, AutoML Tables, Model export, Prediction functions.
Answered from the vendors’ own pages
Arize AI: What does Arize AX cost?
Arize AX offers a free plan, a Pro plan at $50/month, and a custom-priced Enterprise plan, with pricing based on trace spans, storage, and retention needs.
SourceBigQuery 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.
SourceArize AI: Is there a free plan, and what are its limits?
The AX Free plan includes 25,000 trace spans and 1 GB of storage per month with 15-day retention, plus unlimited users, evaluations, and experiments.
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.
SourceArize AI: What deployment options are available?
Free and Pro plans are SaaS-only, while Enterprise customers can choose SaaS or self-hosted deployment with custom SLAs.
SourceRelated pages
More on BigQuery ML
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