As companies revamp their data architecture for multicloud as they upgrade their data architecture, they’re turning towards cloud data services in order to gain the flexibility they need. These services process, ingest, and connect multiple data sources across multiple platforms to provide consistent high-performance analytics.

Infrastructure-as-a-Service (IaaS): Companies rent computing resources, like virtual servers, storage and database software, through a cloud service provider. This means that they do not have to build and manage important source their own infrastructure data centers, which can save energy, time and money. IaaS solutions are flexible enough to accommodate a variety of workloads, ranging from large and small databases to compute-optimized or memory-optimized instances, as required.

Storage-as a Service (SaaS). SaaS solutions allow you to store data remotely, in logical pools. You can access them through a mobile application or a web-browser. Businesses pay for the storage they use within the course of a particular month quarter, year, or even year.

Function-as-a-Service (FaaS): FaaS allows developers to run code for applications and back-end services without the need to provision or manage servers. Cloud service providers can scale up or down computing capacity in real time to meet demand. They charge for the execution of the application code. This is similar to renting out a house, where you pay only for the rooms when you’re eating or watching television, and not all at once.

Cloud data services are accessible on multiple private clouds or the public cloud. They also provide first-party integrations that speed up data analysis. They’re also protected by default and come with advanced compliance, redundancy and recovery and reliability capabilities.