As organizations increasingly adopt public cloud solutions for their IT infrastructure, they face challenges in database migration and management, making Database as a Service (DBaaS) an attractive option. This approach simplifies tasks like provisioning, administration, and security, and while AWS and Google Cloud Platform offer similar DBaaS services, they have distinct features catering to different needs. AWS's Relational Database Service (RDS) supports multiple database engines with flexible scaling, whereas Google Cloud SQL is more straightforward but with limited engine support. For NoSQL solutions, Amazon offers DynamoDB, while Google provides Cloud Datastore and Cloud Bigtable, each with unique scaling capabilities and database models. Data warehousing solutions like Amazon Redshift and Google BigQuery offer robust analytics capabilities, although they differ in management and scalability approaches, with BigQuery being serverless. The trend toward serverless DBaaS, exemplified by BigQuery, minimizes management overhead and shifts focus towards business insights, potentially redefining how cloud infrastructure is monitored.