Architecting Data-Intensive SaaS Applications

Chapter 6. Summary and Further Reading

Data applications are uniquely positioned to drive customer success and create new sources of revenue by taking advantage of modern data platforms. After decades of being held back by legacy technology, business needs are now in the driver’s seat, providing fertile ground for innovation.

Data applications make data actionable through processing large volumes of complex, fast-changing data and providing customers with analytics capabilities to harness their data directly within the application. These applications need to handle all types of data and be flexible enough to accommodate changes in data sources while surfacing new data as quickly as possible to customers in a scalable compute environment.

Traditional data platforms lack the flexibility of modern, cloud-first approaches, making it difficult to use them to build successful data applications. In this report you’ve learned what to look for in a modern data platform to offload the data management burden from product teams so they can focus on building applications. Key components of these platforms include:

Cloud-first architecture

Cloud-first data platforms maximize the advantages of modern technology, providing near-infinite storage and compute resources to support multiple tenants and workloads, and elasticity that guarantees SLAs in times of peak demand and keeps costs low when demand is low.

Separation of storage and compute

Decoupling storage and compute maximizes the benefits ...