1960s-1980s: Mainframe

Mainframes and Minicomputers: This era saw the rise of enterprise software with companies like IBM dominating the market. Software was often custom-built and expensive, primarily serving large organizations.

Early Internet (ARPANET): The foundation of the internet was laid, primarily used for research and academic purposes.

1980s-1990s: PC, RDBMS, and Client-Server

PCs brought computing power to individual users. Distributed computing with applications running on both PCs and servers. RDBMS became more accessible (e.g., SQL Server, Sybase) and thrived in the client-server model. The internet became publicly accessible, opening doors for new applications.

Mid 2000s - 2020s: Cloud and SaaS

Cloud Computing takes center stage during this era. AWS pioneered public cloud computing, providing on-demand access to IT resources. Cloud infrastructure fueled the rapid growth of SaaS applications.

RDBMS became available as a fully managed service (e.g., Amazon RDS, Azure SQL Database) without clients having to host DBs on their own. More and more SaaS applications started getting integrated with mobile devices and social media platforms. Big Data and Analytics: Cloud data warehouses and NoSQL databases worked together to handle the growing volume and variety of data.

2020s - Beyond: AI

AI and ML are being embedded into SaaS and cloud-based applications. AI-driven databases now lay the foundation for more intelligent computing compared to DBs from the previous generation, transforming content creation, customer service, and other business functions. AI enables businesses to tailor experiences to individual customers and employees. More custom software is being developed for companies a lot faster at a cheaper rate.

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The Era of AI vs Cloud

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The Era of AI vs Cloud