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Databases · head to head

Amazon Aurora vs Google Vertex AI

Amazon Aurora logo

Amazon Aurora

Databases

MySQL and PostgreSQL-compatible relational database built for the cloud

From
Free
Rated
-
Full reviewWebsite
Google Vertex AI logo

Google Vertex AI

Machine Learning

Unified ML platform to build, deploy, and scale AI models

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Amazon Aurora has a free tier, so it costs nothing to try first.
  • Each has a real cost: Amazon Aurora aurora requires AWS ecosystem knowledge and integration with other AWS services; Google Vertex AI vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • They diverge on capability: Amazon Aurora covers MySQL/PostgreSQL Compatible, Google Vertex AI covers AutoML.

Where they differ

Only the attributes on which Amazon Aurora and Google Vertex AI actually diverge.

Attributes where Amazon Aurora and Google Vertex AI differ
AttributeAmazon AuroraGoogle Vertex AI
Starting priceFreeOn request
Pricing modelusage-basedUnknown
Free tierYesNo
PlatformsAWS CloudCloud, Web
CategoryDatabasesMachine Learning
Founded20062008

Identical on both: 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 Amazon Aurora

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

Only in Google Vertex AI

  • AutoML
  • Custom training
  • Feature Store
  • Model monitoring
  • Prediction serving
  • BigQuery
  • Cloud Storage
  • TensorFlow

Both cover

  • Web support

What people use each for

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

Amazon Aurora

  • Transaction processingnot Google Vertex AI
  • Data storagenot Google Vertex AI
  • Application backendnot Google Vertex AI
  • Reportingnot Google Vertex AI
  • Data analyticsnot Google Vertex AI

Google Vertex AI

  • 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

Google Vertex AI

  • Vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • Requires familiarity with Google Cloud Platform infrastructure and concepts
  • Cost can escalate quickly with large training and inference workloads

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

Google Vertex AI

On request

No published plan breakdown. See the Google Vertex AI 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 Google Vertex AI if

  • You need automl.
  • You work on Cloud, Web.
  • You also want custom training.
Google Vertex AI review

Questions people ask

Is Amazon Aurora or Google Vertex AI better?
Neither clearly leads. Amazon Aurora starts at Free and Google Vertex AI at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon Aurora or Google Vertex AI?
Amazon Aurora has a free tier; the other does not. Paid plans start at Free for Amazon Aurora and On request for Google Vertex AI.
Does Amazon Aurora or Google Vertex AI run on more platforms?
Amazon Aurora runs on AWS Cloud. Google Vertex AI runs on Cloud, Web.
Can I use Amazon Aurora for free?
Yes. Amazon Aurora has a free tier, so you can try it without paying. Google Vertex AI starts at On request.
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 Google Vertex AI is typically brought in for.
What can Amazon Aurora do that Google Vertex AI cannot?
Amazon Aurora covers MySQL/PostgreSQL Compatible, 5x MySQL Performance, Auto-scaling Storage, Global Database. Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring. Both handle 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
Google Vertex AI: What is the pricing model for Google Vertex AI?

Vertex AI uses a pay-as-you-go model with no upfront costs or lock-in fees. Costs vary by service: training is billed by compute resources and time (30-second increments), online predictions by machine type per hour, and batch predictions by compute time or per-record for specific AutoML types.

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
Google Vertex AI: What types of data can Vertex AI handle?

Vertex AI supports image, video, text, and tabular data types with tools for uploading, storing, and managing large datasets.

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
Google Vertex AI: Does Vertex AI support custom model training?

Yes. Vertex AI supports both AutoML for automated machine learning and custom training code in Python, R, and other languages.

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
Google Vertex AI: What deployment options are available in Vertex AI?

Vertex AI supports online predictions for real-time use cases and batch predictions for large-scale processing.

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
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