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Machine Learning · head to head

Google Vertex AI vs PlanetScale

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
PlanetScale logo

PlanetScale

Databases

The MySQL-compatible serverless database

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only PlanetScale has a free tier, so it costs nothing to try first.
  • Each has a real cost: Google Vertex AI vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult; PlanetScale pricing varies significantly across 17+ AWS and GCP regions
  • They diverge on capability: Google Vertex AI covers AutoML, PlanetScale covers Database Branching.

Where they differ

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

Attributes where Google Vertex AI and PlanetScale differ
AttributeGoogle Vertex AIPlanetScale
Starting priceOn requestFree
Pricing modelUnknownusage-based
Free tierNoYes
PlatformsCloud, WebCloud-hosted (AWS, GCP, Azure)
CategoryMachine LearningDatabases
Founded20082018

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 Google Vertex AI

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

Only in PlanetScale

  • Database Branching
  • Non-blocking Schema Changes
  • Insights
  • Horizontal Scaling
  • Connection Pooling
  • Query Caching
  • Automatic Backups
  • Global Replication

Both cover

  • Web support

What people use each for

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

Google Vertex AI

  • Machine learningnot PlanetScale
  • Data analysisnot PlanetScale
  • Model trainingnot PlanetScale
  • Predictive analyticsnot PlanetScale

PlanetScale

  • MySQL-compatible applications requiring horizontal scalingnot Google Vertex AI
  • PostgreSQL deployments with custom cluster configurationsnot Google Vertex AI
  • Multi-region database deployments on AWS or GCPnot Google Vertex AI
  • Applications requiring transparent sharding via Vitessnot Google Vertex AI

Where each one falls short

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

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

PlanetScale

  • Pricing varies significantly across 17+ AWS and GCP regions
  • Additional costs for EBS storage beyond base tier, backup storage, and egress
  • Dedicated PgBouncer and replicas incur separate charges
  • Metal tier pricing increases sharply with larger configurations

Pricing, plan by plan

Google Vertex AI

On request

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

PlanetScale

Free
  • Postgres EBS Single-Node (ARM64 PS-5)$5/month
    • 512 MiB RAM
    • Single-node configuration
    • EBS storage included
  • Postgres EBS HA (ARM64 PS-5)$15/month
    • 512 MiB RAM
    • 3-node high-availability setup
    • 1 primary + 2 replicas
  • Postgres Metal (M-10)$50/month
    • 1/8 vCPU, 1 GiB RAM
    • 3-node HA configuration
    • 10 GiB NVMe storage included
  • Vitess Non-Metal 3-Node$39/month
    • Sharding-capable database
    • x86-64 architecture
    • 3-node configuration

Which should you pick?

Choose Google Vertex AI if

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

Choose PlanetScale if

  • You need database branching.
  • You want to start without paying.
  • You work on Cloud-hosted (AWS, GCP, Azure).
  • You also want non-blocking schema changes.
PlanetScale review

Questions people ask

Is Google Vertex AI or PlanetScale better?
Neither clearly leads. Google Vertex AI starts at On request and PlanetScale at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Google Vertex AI or PlanetScale?
PlanetScale has a free tier; the other does not. Paid plans start at On request for Google Vertex AI and Free for PlanetScale.
Does Google Vertex AI or PlanetScale run on more platforms?
Google Vertex AI runs on Cloud, Web. PlanetScale runs on Cloud-hosted (AWS, GCP, Azure).
Can I use PlanetScale for free?
Yes. PlanetScale has a free tier, so you can try it without paying. Google Vertex AI starts at On request.
What is Google Vertex AI best used for?
Google Vertex AI is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what PlanetScale is typically brought in for.
What can Google Vertex AI do that PlanetScale cannot?
Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring. PlanetScale covers Database Branching, Non-blocking Schema Changes, Insights, Horizontal Scaling. Both handle Web support.

Answered from the vendors’ own pages

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
PlanetScale: How much does a PlanetScale Postgres database cost per month?

PlanetScale Postgres pricing starts at $5/month for single-node ARM64 configurations with 512 MiB RAM and $15/month for the same specs in high-availability mode with 1 primary and 2 replicas. Metal tier starts at $50/month for M-10 configuration (1/8 vCPU, 1 GiB RAM). Exact pricing depends on cluster size, node architecture (ARM64 vs x86-64), storage configuration, and selected AWS/GCP region.

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
PlanetScale: Is there a free tier for PlanetScale?

PlanetScale offers a free tier for development and testing workloads. After free tier limits are reached, usage-based pricing applies starting at $5/month for the smallest Postgres single-node configuration, with costs scaling based on cluster size, compute, storage, and additional features like dedicated PgBouncer or replicas.

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
PlanetScale: What is the difference between PlanetScale ARM64 and x86-64 pricing?

ARM64 instances cost significantly less than x86-64 equivalents. For example, a Postgres EBS HA cluster with 512 MiB RAM costs $15/month on ARM64 but $39/month on x86-64. This pricing difference extends across all cluster sizes, with larger x86-64 configurations reaching up to $5,599/month compared to ARM64 alternatives.

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
PlanetScale: What is included in a PlanetScale cluster price versus additional costs?

The advertised cluster price covers the base compute and configured storage. Additional charges apply for EBS storage beyond the base allocation, backup storage, data egress, optional dedicated PgBouncer connections, and replicas beyond the base high-availability configuration. Regional pricing varies across 17+ AWS and GCP zones.

Source
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