Page Comparison

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• AWS: For Kubernetes, Kyvos processes the semantic model using Amazon Elastic Kubernetes Service (Amazon EKS). You can select Query Engine or Kubernetes as a compute engine using no Spark model processing.
  For further details about deployment, see the Automated deployment for AWS via CloudFormation with Kyvos Native section.

• Azure: For Kubernetes, Kyvos processes the semantic model using Azure’s managed service AKS (Azure Kubernetes Service).

  • The Azure cluster is deployed via ARM templates. You can create a cluster without Spark or process the semantic model using Spark mode within ARM templates.
    For further details about deployment, see the Automated deployment on Azure with Kyvos Native section.

  • From Kyvos 2024.3 onwards, you can select the compute cluster as the Query engine or Kubernetes when deploying Kyvos through Azure Template Specs.

• GCP: For Kubernetes, Kyvos processes the semantic model using Google Cloud's managed service GKE (Google Kubernetes Engine). The GKE cluster is deployed through GCP Installation Files. Using the scripts, you can select a No-Spark-based cluster or process the semantic model using Spark Mode.
  Optionally, for no-Spark deployments, you can either use new or existing Dataproc cluster.
  For further details about Kyvos deployment on GCP using the no-Spark model, see the following section:

  • Prerequisites to deploy Kyvos using Kubernetes

  • Creating Kyvos Resources for GCP using Script

• On Premises: For On-premises deployment, you can deploy using No Spark types: SHARED_QE and Compute Server. For further details about on premises deployment with no-Spark, see the Deploying no Hadoop no Spark.

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