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المحتوى المقدم من Dan Vega and DaShaun Carter. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Dan Vega and DaShaun Carter أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
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S4E19 - Spring & Redis with Raphael De Lio

1:02:16
 
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Manage episode 494571753 series 3470589
المحتوى المقدم من Dan Vega and DaShaun Carter. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Dan Vega and DaShaun Carter أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

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.

  continue reading

92 حلقات

Artwork
iconمشاركة
 
Manage episode 494571753 series 3470589
المحتوى المقدم من Dan Vega and DaShaun Carter. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Dan Vega and DaShaun Carter أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

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.

  continue reading

92 حلقات

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