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Elastic Stack vs Google Vertex AI

Elastic Stack logo

Elastic Stack

Logging

Search, Observability, and Security Solutions

From
On request
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: Elastic Stack self-managed deployment requires licensing based on node count and RAM usage; Google Vertex AI vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • They diverge on capability: Elastic Stack covers Full-text search, Google Vertex AI covers AutoML.

Where they differ

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

Attributes where Elastic Stack and Google Vertex AI differ
AttributeElastic StackGoogle Vertex AI
Pricing modelsubscriptionUnknown
PlatformsCloud-hosted, Self-managed, Docker, Kubernetes (ECK)Cloud, Web
CategoryLoggingMachine Learning
Founded20112008

Identical on both: starting price (On request), 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 Elastic Stack

  • Full-text search
  • Log analytics
  • Security monitoring
  • Alerting
  • API
  • Webhooks
  • REST
  • Api support

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.

Elastic Stack

  • Distributed search and analytics engine for production-scale workloadsnot Google Vertex AI
  • Full-text search and vector search with approximate nearest neighbour supportnot Google Vertex AI
  • Security event tracking with field-level and document-level access controlnot Google Vertex AI
  • Machine learning capabilities including anomaly detection and forecastingnot Google Vertex AI

Google Vertex AI

  • Machine learningnot Elastic Stack
  • Data analysisnot Elastic Stack
  • Model trainingnot Elastic Stack
  • Predictive analyticsnot Elastic Stack

Where each one falls short

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

Elastic Stack

  • Self-managed deployment requires licensing based on node count and RAM usage
  • Serverless option has pending features including traffic filtering and bring-your-own-key encryption
  • Hosted deployment requires custom resource configuration for cluster management
  • Pricing models differ significantly across Hosted, Serverless, and Self-managed options

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

Elastic Stack

On request

No published plan breakdown. See the Elastic Stack review.

Google Vertex AI

On request

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

Which should you pick?

Choose Elastic Stack if

  • You need full-text search.
  • You work on Cloud-hosted, Self-managed, Docker, Kubernetes (ECK).
  • You also want log analytics.
Elastic Stack 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 Elastic Stack or Google Vertex AI better?
Neither clearly leads. Elastic Stack starts at On request 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, Elastic Stack or Google Vertex AI?
Elastic Stack starts at On request and Google Vertex AI at On request.
Does Elastic Stack or Google Vertex AI run on more platforms?
Elastic Stack runs on Cloud-hosted, Self-managed, Docker, Kubernetes (ECK). Google Vertex AI runs on Cloud, Web.
What is Elastic Stack best used for?
Elastic Stack is most often used for distributed search and analytics engine for production-scale workloads, full-text search and vector search with approximate nearest neighbour support, security event tracking with field-level and document-level access control, machine learning capabilities including anomaly detection and forecasting. Of those, distributed search and analytics engine for production-scale workloads and full-text search and vector search with approximate nearest neighbour support are not what Google Vertex AI is typically brought in for.
What can Elastic Stack do that Google Vertex AI cannot?
Elastic Stack covers Full-text search, Log analytics, Security monitoring, Alerting. Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring. Both handle Web support.

Answered from the vendors’ own pages

Elastic Stack: How much does Elastic Stack cost?

Elastic does not publish specific pricing on the Elastic Stack product page. Users can start a 14-day free trial with no credit card required, but ongoing subscription pricing requires contacting their sales team.

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
Elastic Stack: What deployment options are available for Elastic Stack?

Users can deploy Elastic Stack on Elastic Cloud (hosted on AWS, Google Cloud, or Azure) or download it for self-managed deployment. Pricing for managed cloud hosting must be obtained by starting a trial or contacting sales.

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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