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Software · head to head

Google Vertex AI vs Redash

Google Vertex AI logo

Google Vertex AI

Software

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

From
On request
Rated
-
Full reviewWebsite
Redash logo

Redash

Software

Connect and visualize your data

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Redash 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; Redash a basic self-hosted deployment needs a minimum of 4GB of RAM, and more RAM and CPU as background workers and API processes grow
  • They diverge on capability: Google Vertex AI covers AutoML, Redash covers SQL Query Editor.

Where they differ

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

Attributes where Google Vertex AI and Redash differ
AttributeGoogle Vertex AIRedash
Starting priceOn requestFree
Pricing modelUnknownfreemium
Free tierNoYes
PlatformsCloud, WebWeb, Self-hosted, Cloud
Founded20082013

Identical on both: user rating (Not yet rated), category (Unknown).

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
  • Cloud Storage
  • TensorFlow
  • PyTorch

Only in Redash

  • SQL Query Editor
  • Multiple Data Sources
  • Visualizations
  • Dashboards
  • Alerts
  • PostgreSQL
  • MySQL
  • Redshift

Both cover

  • BigQuery
  • Web support

What people use each for

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

Google Vertex AI

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

Redash

  • Self-hosted SQL query editor and dashboarding over existing databasesnot Google Vertex AI
  • Sharing scheduled query results with a team without buying a BI licencenot 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

Redash

  • A basic self-hosted deployment needs a minimum of 4GB of RAM, and more RAM and CPU as background workers and API processes grow
  • The official Docker images were not updated for V10, so the documented route is to deploy a V8 instance and then upgrade it
  • Anyone not using a provided cloud image has to configure the environment variables and secrets by hand

Pricing, plan by plan

Google Vertex AI

On request

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

Redash

Free
  • Open SourceFree
    • Full Features
    • Self-hosted
    • Community Support
  • Cloud$49/month
    • Managed Hosting
    • Automatic Updates
    • Support

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 Redash if

  • You need sql query editor.
  • You want to start without paying.
  • You work on Web, Self-hosted, Cloud.
  • You also want multiple data sources.
Redash review

Questions people ask

Is Google Vertex AI or Redash better?
Neither clearly leads. Google Vertex AI starts at On request and Redash at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Google Vertex AI or Redash?
Redash has a free tier; the other does not. Paid plans start at On request for Google Vertex AI and Free for Redash.
Does Google Vertex AI or Redash run on more platforms?
Google Vertex AI runs on Cloud, Web. Redash runs on Web, Self-hosted, Cloud.
Can I use Redash for free?
Yes. Redash 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 Redash is typically brought in for.
What can Google Vertex AI do that Redash cannot?
Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring. Redash covers SQL Query Editor, Multiple Data Sources, Visualizations, Dashboards. Both handle BigQuery, 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
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
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
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
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