Redis, originally developed as an in-memory caching and message brokering solution, has evolved into a complex ecosystem with various editions and adaptations, including cloud-based services on platforms like AWS and Azure. While Redis is celebrated for its ease of use and performance in small-scale applications, its scalability is limited by its reliance on expensive RAM, single-threaded data access, and cumbersome horizontal scaling. These limitations can lead to high costs and operational challenges, especially as applications grow in data volume or user base. Additionally, Redis's persistence options, such as RDB snapshots and Append-Only Files, introduce latency and are less reliable than those of databases designed with persistence in mind. The lack of robust clustering and replication mechanisms further complicates scaling and data management. Developers are encouraged to consider more elastic and durable database management systems (DBMS) from the outset, which can better accommodate growth without necessitating costly migrations or refactoring. The discussion highlights alternatives like Aerospike, which offer integrated memory and flash storage solutions and superior elasticity, addressing the limitations inherent in Redis for large-scale, data-intensive applications.