Softwr

Databases · head to head

Amazon Aurora vs AWS SageMaker

Amazon Aurora logo

Amazon Aurora

Databases

MySQL and PostgreSQL-compatible relational database built for the cloud

From
Free
Rated
-
Full reviewWebsite
AWS SageMaker logo

AWS SageMaker

Machine Learning

Build, train, and deploy machine learning models at scale

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Amazon Aurora aurora requires AWS ecosystem knowledge and integration with other AWS services; AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult
  • They diverge on capability: Amazon Aurora covers MySQL/PostgreSQL Compatible, AWS SageMaker covers Jupyter notebooks.

Where they differ

Only the attributes on which Amazon Aurora and AWS SageMaker actually diverge.

Attributes where Amazon Aurora and AWS SageMaker differ
AttributeAmazon AuroraAWS SageMaker
Pricing modelusage-basedUnknown
PlatformsAWS CloudWeb
CategoryDatabasesMachine Learning

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), founded (2006).

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 Amazon Aurora

  • MySQL/PostgreSQL Compatible
  • 5x MySQL Performance
  • Auto-scaling Storage
  • Global Database
  • Serverless v2
  • Multi-master
  • Fault Tolerant
  • AWS Lambda

Only in AWS SageMaker

  • Jupyter notebooks
  • Built-in algorithms
  • Automatic model tuning
  • One-click deployment
  • Model monitoring
  • Lambda
  • Step Functions
  • ECR

Both cover

  • S3
  • CloudWatch
  • Web support

What people use each for

The jobs each tool is most often brought in to do.

Amazon Aurora

  • Transaction processingnot AWS SageMaker
  • Data storagenot AWS SageMaker
  • Application backendnot AWS SageMaker
  • Reportingnot AWS SageMaker
  • Data analyticsnot AWS SageMaker

AWS SageMaker

  • Machine learningnot Amazon Aurora
  • Data analysisnot Amazon Aurora
  • Model trainingnot Amazon Aurora
  • Predictive analyticsnot Amazon Aurora

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Amazon Aurora

  • Aurora requires AWS ecosystem knowledge and integration with other AWS services
  • Pricing can become expensive with high-traffic applications using many read replicas
  • Limited support for non-relational data types compared to NoSQL alternatives

AWS SageMaker

  • Vendor lock-in to AWS ecosystem makes migration to other platforms difficult
  • Opaque pricing can lead to unexpected expenses like forgotten EBS volume charges
  • Does not include native job scheduling, requiring Lambda or EventBridge integration

Pricing, plan by plan

Amazon Aurora

Free
  • Serverless v2$0.12/hour
    • Auto-scaling
    • Pay per ACU
    • Instant scaling
  • Provisioned$29/month
    • Dedicated instances
    • Predictable performance
    • Reserved capacity

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker review.

Which should you pick?

Choose Amazon Aurora if

  • You need mysql/postgresql compatible.
  • You want to start without paying.
  • You work on AWS Cloud.
  • You also want 5x mysql performance.
Amazon Aurora review

Choose AWS SageMaker if

  • You need jupyter notebooks.
  • You want to start without paying.
  • You also want built-in algorithms.
AWS SageMaker review

Questions people ask

Is Amazon Aurora or AWS SageMaker better?
Neither clearly leads. Amazon Aurora starts at Free and AWS SageMaker at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon Aurora or AWS SageMaker?
Amazon Aurora starts at Free and AWS SageMaker at Free.
Does Amazon Aurora or AWS SageMaker run on more platforms?
Amazon Aurora runs on AWS Cloud. AWS SageMaker runs on Web.
Can I use Amazon Aurora for free?
Both have a free tier, so you can try either at no cost before committing.
What is Amazon Aurora best used for?
Amazon Aurora is most often used for transaction processing, data storage, application backend, reporting. Of those, transaction processing and data storage are not what AWS SageMaker is typically brought in for.
What can Amazon Aurora do that AWS SageMaker cannot?
Amazon Aurora covers MySQL/PostgreSQL Compatible, 5x MySQL Performance, Auto-scaling Storage, Global Database. AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Both handle S3, CloudWatch, Web support.

Answered from the vendors’ own pages

Amazon Aurora: Is Amazon Aurora compatible with MySQL and PostgreSQL?

Yes, Amazon Aurora offers MySQL and PostgreSQL compatibility with full compatibility to their open-source counterparts, allowing you to migrate existing databases with standard tools.

Source
AWS SageMaker: What is AWS SageMaker used for?

AWS SageMaker is a machine learning service for building, training, and deploying ML models at scale. It provides tools for data preparation, model training, inference endpoints, and performance optimization.

Source
Amazon Aurora: What uptime SLA does Amazon Aurora provide?

Aurora is designed for up to 99.99% single-region uptime and 99.999% multi-region uptime with automatic failover.

Source
AWS SageMaker: How is AWS SageMaker priced?

SageMaker uses pay-as-you-go pricing with no upfront costs or long-term commitments. Pricing starts at $0.04 per hour for basic notebook instances and scales based on instance type. ML Savings Plans offer up to 64% off with hourly spend commitments.

Source
Amazon Aurora: How much does Amazon Aurora cost?

Aurora uses serverless, usage-based pricing where you pay only for consumed capacity. Typical pricing ranges from $50-70 per month for minimal setups to $400-600 per month for small production clusters.

Source
AWS SageMaker: Does AWS SageMaker have a free tier?

Yes, the free tier includes 250 hours of notebook usage, 50 hours of training, and 125 hours of hosting on ml.t3.medium instances during the first two months.

Source
Amazon Aurora: Can Amazon Aurora scale automatically?

Yes, Aurora automatically scales to match workload demands without performance degradation, supporting both read and write scaling.

Source
Amazon Aurora: How many read replicas does Aurora support?

Aurora supports up to 15 low-latency read replicas for distributing read traffic across your application.

Source
Share

Related pages

More on Amazon Aurora

More on AWS SageMaker

Keep looking

Other head to heads