Category: Amazon ElastiCache

Amazon receives millions of visits every day, and earning each customer’s trust visit after visit is the foundation that the store is built on. A meaningful part of that trust comes down to whether the recommendations we surface feel relevant and whether they reflect what the customer actually cares about in the moment. In this post, we describe an architecture that makes it achievable. Amazon SageMaker hosts a sentence transformer model on a managed endpoint and turns customer query text into dense semantic vectors. Valkey is an open source, in-memory data store with built-in vector search. It’s available on AWS through Amazon ElastiCache and Amazon MemoryDB. In our architecture, we use Amazon-managed Valkey to store the product catalog as a vector index.

In this post we demonstrate how Nine Entertainment achieved a 98% cost reduction by migrating to Amazon ElastiCache Serverless for Valkey while improving scalability and eliminating manual intervention during peak events.

Today, we’re announcing the Remote Query Cache Plugin for the AWS Advanced JDBC Wrapper. The plugin handles query caching automatically. It intercepts JDBC queries, caches results in Amazon ElastiCache for Valkey, and serves subsequent identical queries from cache. Your only application change is prefixing queries with SQL hints. In this post, we show you how to use Amazon CloudWatch Database Insights to identify queries to cache, configure the Remote Query Cache Plugin in your Java applications, and monitor cache effectiveness using Amazon CloudWatch.

In this post, you learn how HotelTrader reduced inter-availability zone data transfer costs by 95% and improved average latency by 49% by migrating from the Redis Lettuce client to Valkey GLIDE on Amazon ElastiCache. The post walks through how HotelTrader identified hidden cross-AZ data transfer costs in their multi-AZ ElastiCache cluster, implemented Valkey GLIDE’s AZ-affinity read strategy to route requests to local replicas, optimized throughput with request batching, and executed a zero-downtime migration using A/B testing over 15 days.

Amazon ElastiCache now supports Valkey 9.0. This brings the latest community-driven innovations from the Valkey open source project to address the performance and capability requirements of applications as they grow more data-intensive and latency-sensitive, such as real-time analytics, AI-driven retrieval, and high-throughput caching. In this post, we explore how these enhancements help customers build faster applications, streamline architectures, and support new real-time and AI-driven workloads.

New search capabilities are available in ElastiCache version 9.0 for Valkey. In this post, we walk through the new search capabilities, show how they work together, and build a search and recommendation engine from scratch.

Amazon ElastiCache now supports aggregation queries, so you can filter, group, transform, and summarize data directly in your cache with a single query. This post walks through the use cases that aggregations unlock, and shows how they work by building a faceted browsing engine using Amazon ElastiCache for Valkey.

Two years ago, Valkey emerged as a community-driven response to the need for a truly open, vendor-neutral alternative to Redis. In this post, we’ll look back at two years of progress, highlighting the rapid adoption of Valkey, the innovations delivered by the community, and what these developments mean for the future of modern caching and […]

This post addresses recovery challenges in multi-database architectures, focusing on both low-consistency and mission-critical scenarios. We explore practical strategies for implementing resilient recovery mechanisms across Amazon DynamoDB, Amazon Aurora, Amazon Neptune, Amazon OpenSearch Service, and other AWS database services.

In this post, we provide a guide to migrating from Redis OSS to ElastiCache for Valkey, incorporating different migration strategies and AWS best practices. Additionally, we highlight a customer’s successful migration to Valkey, which maintained their robust performance standards while achieving a 20% reduction in ElastiCache cluster costs.