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Season 4, Episode 19July 15, 2025Duration: 1h 2m 16s

Spring & Redis with Raphael De Lio

Dan and DaShaun are joined by Redis Developer Advocate, Raphael De Lio. Join us as we explore Redis’s ever-growing role in the Spring ecosystem. We will look discuss its common and foundational use cases, then dig into new and exciting use cases, including similarity search, the cutting-edge vector data type, and how Redis is becoming a key player in AI-driven solutions. Get ready to discover the latest ways Spring developers are leveraging Redis to build highly performant and intelligent applications. Key Takeaways What is Redis? Originally created in 2009 as a fast, horizontally scalable database Known primarily for caching, but it's actually a full database with persistence and transactions Redis 8 is now open source again with massive performance improvements (87% faster execution, 2x higher throughput) Beyond Caching: Redis Use Cases Vector databases for AI applications (semantic search, caching, routing) Time series data for real-time analytics Geospatial indexing for location-based features Probabilistic data structures (Bloom filters, count-min sketch) for high-scale applications Streams for message queues and real-time data processing Session storage for distributed applications AI & Vector Database Applications Semantic caching : Cache LLM responses using vector similarity (can reduce costs by 60%) Semantic routing : Route queries to appropriate tools without calling LLMs Memory for AI agents : Short-term and long-term conversation memory Recommendation systems : Power Netflix/YouTube-style recommendations Getting Started with Spring Use start.spring.io with Docker Compose for easy setup Spring Data Redis for basic caching with @Cacheable Redis OM Spring for advanced features (vector search, JSON, etc.) New annotations: @Vectorize and @Indexed for automatic vector embeddings Upcoming Events Spring One - 6 weeks away in Las Vegas Redis Hackathon - July 23rd via dev.to/challenges Links & Resources Redis Redis OM Spring Redis YouTube Channel Spring One Conference Start Spring IO Connect with Raphael DeLeo Email : [email protected] LinkedIn : Raphael DeLeo GitHub : raphaeldelio Blue Sky : raphaeldelio.dev Redis vs Valkey discussion included - Redis 8 returns to open source with significant performance improvements and integrated modules that were previously separate.

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Show Notes

Join Dan Vega and DaShaun Carter for the latest updates from the Spring Ecosystem. In this episode, Dan and DaShaun are joined by Redis Developer Advocate, Raphael De Lio. Join us as we explore Redis’s ever-growing role in the Spring ecosystem.  We will look discuss its common and foundational use cases, then dig into new and exciting use cases, including similarity search, the cutting-edge vector data type, and how Redis is becoming a key player in AI-driven solutions. Get ready to discover the latest ways Spring developers are leveraging Redis to build highly performant and intelligent applications. You can participate in our live stream to ask questions or catch the replay on your preferred podcast platform.

Key Takeaways
What is Redis?
  • Originally created in 2009 as a fast, horizontally scalable database
  • Known primarily for caching, but it's actually a full database with persistence and transactions
  • Redis 8 is now open source again with massive performance improvements (87% faster execution, 2x higher throughput)
Beyond Caching: Redis Use Cases
  • Vector databases for AI applications (semantic search, caching, routing)
  • Time series data for real-time analytics
  • Geospatial indexing for location-based features
  • Probabilistic data structures (Bloom filters, count-min sketch) for high-scale applications
  • Streams for message queues and real-time data processing
  • Session storage for distributed applications
AI & Vector Database Applications
  • Semantic caching: Cache LLM responses using vector similarity (can reduce costs by 60%)
  • Semantic routing: Route queries to appropriate tools without calling LLMs
  • Memory for AI agents: Short-term and long-term conversation memory
  • Recommendation systems: Power Netflix/YouTube-style recommendations
Getting Started with Spring
  • Use start.spring.io with Docker Compose for easy setup
  • Spring Data Redis for basic caching with @Cacheable
  • Redis OM Spring for advanced features (vector search, JSON, etc.)
  • New annotations: @Vectorize and @Indexed for automatic vector embeddings
Upcoming Events
  • Spring One - 6 weeks away in Las Vegas
  • Redis Hackathon - July 23rd via dev.to/challenges
Links & Resources
Connect with Raphael DeLeo
Redis vs Valkey discussion included - Redis 8 returns to open source with significant performance improvements and integrated modules that were previously separate.

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