My talk was about similarity search with #Redis and #RedisOMSpring. Basically, instead of searching for exact matches, you search for meaning and context. And the best part? You can do it with just two annotations: @Vectorize and @Indexed. #javabubble

Uma dica para quem está usando o #SpringDataRedis: Experimentem o #RedisOMSpring.

Essa lib é um fork mantido pela própria #Redis que aumenta as capacidades do Spring Data Redis.

+ Info na thread 🧵

github.com/redis/redis-...

#bolhadev @samsantosb.bsky.social @sseraphini.bsky.social

6/9 5. Redis OM Spring – The data powerhouse
Managing vectors and searching through data needs to be fast and reliable. #RedisOMSpring is built on top of Spring Data and makes working with #Redis a lot easier, especially when dealing with AI-powered searches.

Finally we used the Saturn V Lego Set to understand how this rocket was able to take not only men to space, but also how it could be used as an analogy to accomplish our own mission using #Java, #Redis, #SpringBoot and #RedisOMSpring!

Thank you for the video, Barend Schut!

6/7 The coolest part? As Luigi Fugaro demonstrated in his talk, you don’t have to leave the tools and languages you already love.

You can build AI applications directly in #Java with SpringBoot by simply adding #SpringDataRedis and #RedisOMSpring as dependencies.