Hadoop was introduced in 2008 as a solution to organizations' big data problems and gained popularity due to its promise of scalability and cost-effectiveness. However, many industry experts argue that Hadoop may not be the panacea for big data problems it was hyped up to be. The main reasons include skills shortage, high costs, complexity in getting data out, hiring software engineers is expensive, and Hadoop is not optimized for real-time decision making. These limitations have led to a decrease in Hadoop adoption and growth within existing enterprises.