Softwr

Databases · head to head

Firebolt vs Google Vertex AI

Firebolt logo

Firebolt

Databases

Sub-second analytics at cloud data warehouse scale

From
$1.84/hour
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

  • Each has a real cost: Firebolt compute billed per second on Arm-based processors; small instances still incur measurable costs during idle periods despite auto-stop; Google Vertex AI vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • They diverge on capability: Firebolt covers Sub-second Queries, Google Vertex AI covers AutoML.

Where they differ

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

Attributes where Firebolt and Google Vertex AI differ
AttributeFireboltGoogle Vertex AI
Starting price$1.84/hourOn request
Pricing modelusage-basedUnknown
PlatformsCloud (AWS, GCP, Azure preview), Docker, KubernetesCloud, Web
CategoryDatabasesMachine Learning
Founded20192008

Identical on both: free tier (No), 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 Firebolt

  • Sub-second Queries
  • Sparse Indexes
  • Data Pruning
  • Decoupled Storage/Compute
  • SQL Support
  • Semi-structured Data
  • Workload Isolation
  • Airflow

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.

Firebolt

  • Data analytics teams running gigabyte-to-petabyte datasets with sub-second query requirementsnot Google Vertex AI
  • Real-time business intelligence platforms requiring ACID transactions and snapshot isolationnot Google Vertex AI
  • Applications needing vector search on analytical data for similarity queriesnot Google Vertex AI

Google Vertex AI

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

Where each one falls short

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

Firebolt

  • Compute billed per second on Arm-based processors; small instances still incur measurable costs during idle periods despite auto-stop
  • Storage pass-through charged at $0.0264/GB monthly on compressed data; uncompressed storage could exceed this
  • Azure deployment currently in Preview status; production recommendations unclear
  • Vector indexes limited to float arrays; other data types require alternative indexing strategies
  • Free tier credits ($200) limited; no perpetual free tier for production 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

Pricing, plan by plan

Firebolt

$1.84/hour

No published plan breakdown. See the Firebolt review.

Google Vertex AI

On request

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

Which should you pick?

Choose Firebolt if

  • You need sub-second queries.
  • You work on Cloud (AWS, GCP, Azure preview), Docker, Kubernetes.
  • You also want sparse indexes.
Firebolt 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 Firebolt or Google Vertex AI better?
Neither clearly leads. Firebolt starts at $1.84/hour 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, Firebolt or Google Vertex AI?
Firebolt starts at $1.84/hour and Google Vertex AI at On request.
Does Firebolt or Google Vertex AI run on more platforms?
Firebolt runs on Cloud (AWS, GCP, Azure preview), Docker, Kubernetes. Google Vertex AI runs on Cloud, Web.
What is Firebolt best used for?
Firebolt is most often used for data analytics teams running gigabyte-to-petabyte datasets with sub-second query requirements, real-time business intelligence platforms requiring acid transactions and snapshot isolation, applications needing vector search on analytical data for similarity queries. Of those, data analytics teams running gigabyte-to-petabyte datasets with sub-second query requirements and real-time business intelligence platforms requiring acid transactions and snapshot isolation are not what Google Vertex AI is typically brought in for.
What can Firebolt do that Google Vertex AI cannot?
Firebolt covers Sub-second Queries, Sparse Indexes, Data Pruning, Decoupled Storage/Compute. Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring. Both handle Web support.

Answered from the vendors’ own pages

Firebolt: How does Firebolt's compute billing model work?

Firebolt uses per-second billing with scale-to-zero capability. The smallest S tier costs $1.84 per hour with 8 vCPU and 64GB memory, while the largest 4XL tier costs $58.88 per hour with 256 vCPU. Users only pay when compute is running.

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
Firebolt: What is the cost for data storage on Firebolt?

Storage costs $0.0264 per GB per month on object storage, billed as pass-through cost at cloud provider rates.

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
Firebolt: What free credits or trial does Firebolt offer new users?

New users receive $200 free credits to get started with the platform.

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
Firebolt: Does Firebolt publish pricing for commitment-based discounts?

The pricing FAQ lists a question about commitment-based discounts but does not provide published answers on the pricing page. This requires direct inquiry with sales.

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
Firebolt: What deployment options does Firebolt offer besides managed service?

Firebolt offers self-hosted open source deployment (unlimited) and Bring Your Own Cloud (BYOC) options in addition to managed service.

Source
Share

Related pages

More on Firebolt

More on Google Vertex AI

Keep looking

Other head to heads