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Architecture with Dataiku

Capitalize on your existing infrastructure to deliver results at scale with Dataiku’s powerful, flexible, and open architecture.

 

Support for Cloud or On-Premises

Dataiku runs on-premises or in the cloud — with supported instances on Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure — integrating with native storage and computational layers for each cloud. 

Dataiku’s cloud stacks accelerator tooling comes with managed elastic computation clusters, instance templates, advanced security and more, to make it simple for system administrators to deploy, configure, upgrade, and backup one or several Dataiku instances. 

 

Fully Hosted SaaS Offering

Dataiku Online provides a fully hosted SaaS option built for the modern cloud data stack. 

With pre-built data connectors and integrations with Snowflake, Amazon Redshift, Google BigQuery and more, teams of any size can build and deliver AI projects without having to worry about servers, administration, backups, or upgrades. 

 

Pushdown Execution and CPUs/GPUs

For maximum performance and efficiency on large workloads, Dataiku utilizes a pushdown architecture that allows organizations to take advantage of existing, elastic, and highly scalable computing systems including SQL databases, Spark, Kubernetes, and more. 

Graphical Processing Units (GPUs) can dramatically accelerate certain types of model training, especially deep learning models. Dataiku supports the use of both CPUs and GPUs for model training. 

 

Elastic AI with Kubernetes

Dataiku provides a fully managed Kubernetes solution that is compatible with all of the major cloud container services (Amazon EKS, Google Kubernetes Engine (GKE), and Azure Kubernetes Service (AKS)), as well as with on-premises Kubernetes/Docker clusters. 

Elastic computing using cloud services is often the most cost-effective way to handle large and dynamic loads created by big data analysis and machine learning. 

 

Modular Architecture for Diverse Teams

Dataiku provides modular components for project design, batch process automation, real-time API scoring, and AI governance capabilities. 

This enables different teams to outfit their own Dataiku instances with the combination of server components that best fits their needs, for ultimate flexibility and alignment with business goals. 

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Discover How Dataiku Enables Data Architects

From AI orchestration to smooth operationalization, explore how Dataiku helps data architects.

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Dataiku Architecture Basics

This video presents an overview of Dataiku architecture and how it supports MLOps.

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Data Architecture & Deployment Trends

Review the results of a survey of IT professionals to uncover trends in data architecture in the enterprise.

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