Serverless Computing Benefits
Key advantages of Serverless Computing
Serverless computing is cost-effective as compared to traditional cloud providers.
Serverless architecture simplifies scaling the code. Applications built with a serverless infrastructure will scale automatically as the user base grows or usage increases.
Simplified backend code
FaaS allows creating simple functions that independently perform a single purpose.
Serverless architecture can significantly cut time to market as it helps in building lightweight, flexible applications that can be expanded or updated quickly.
Serverless Computing Components
Although these components share a few similarities, here are the 2 major components of Serverless Computing:
BaaS is a service model where a cloud provider offers backend services such as data storage so that developers can focus on writing front-end code.
Function as a Service (FaaS):
FaaS is the layer that executes specific business logic with the cloud provider providing the level of abstraction in terms of executing the business logic.
Let’s check out some of the popular Serverless databases:
Google Cloud Store
It is a Google App Engine’s document-oriented store offering database component as a standalone service. The service combines the performance and scalability of Google’s cloud with advanced security and sharing capabilities.
Fauna is a flexible, developer-friendly, transactional database available as a secure, cloud API with native GraphQL. Fauna takes care of database provisioning, maintenance, scaling, sharding, replication, or correctness.
DynamoDB is an entirely managed NoSQL database service able to provide predictable and high-speed performance with seamless scalability. It allows storing and retrieving any amounts of data, and it’s also able to serve any level or requested traffic.
Amazon Aurora Serverless
Amazon Aurora serverless database is fully-managed and automatically scales to up to 64 terabytes of database storage. It comes in two different editions compatible with both MySQL or PostgreSQL, but it is also compatible with other known systems.
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