What is Cloud-Native Data Platforms

Definition

Cloud-native data platforms are data systems designed specifically for the cloud, using managed services, elastic scaling, separation of storage and compute, and pay-as-you-go pricing, so organisations gain scalable, resilient data capabilities without managing underlying infrastructure.

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Scale storage and compute independently and elastically with demand
Reduce operational burden through fully managed cloud services
Lower cost with consumption-based pricing and no idle hardware
Improve resilience through built-in redundancy and managed failover

Real World Example

A retailer rebuilds its analytics on a cloud-native platform where compute clusters scale up for month-end reporting and shut down afterward, while data sits in cheap object storage, replacing a fixed on-premise cluster.

FAQs

What makes a data platform cloud-native?

It is built for the cloud, using managed services, elastic scaling, separated storage and compute, and consumption-based pricing.

How does separation of storage and compute help?

It lets each scale independently, so you can add compute for heavy queries without paying for it when idle.

What are examples of cloud-native data platforms?

Snowflake, BigQuery, Databricks, and Microsoft Fabric are leading cloud-native data platforms.