These are also closely related to: "Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot"

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  How Plume scaled its database to manage 500M+ smart devices

  By: Amazon Web Services

  Type: Case Study

  Plume, a leader in smart home services, faced database scalability challenges managing over half a billion devices globally. The company migrated from MongoDB to Amazon DocumentDB, a fully managed service compatible with MongoDB workloads. This move significantly increased scalability, allowing Plume to handle 50,000 API calls per minute effortlessly.

  Key benefits included:

  • Reduced need for in-house database management
  • Cost savings equivalent to 3-5 Silicon Valley salaries
  • Decreased latency and improved security
  • Seamless integration with minimal code changes

  AWS collaboration provided valuable insights and support, enabling Plume to focus on delivering flawless wireless internet experiences.

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  Boost database performance and reduce costs with caching

  By: Amazon Web Services

  Type: White Paper

  This white paper explores how Amazon ElastiCache for Redis can optimize costs and boost performance for Amazon RDS for MySQL databases. Key benefits include:

  • Cost savings of up to 55% compared to RDS read replicas
  • Up to 80x faster read performance
  • Handling hundreds of millions of operations per second with microsecond response times
  • Scalability for growing workloads

  The paper outlines caching strategies like lazy loading and write-through caching, and provides examples of cost savings and performance improvements. It explains how ElastiCache complements databases by offloading read operations and reducing the need for read replicas.

  Enhance performance while optimizing costs by reading this.

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