What's the source that they're falling behind? If this is the case, imo Elastic should be able to catch up, as AI algorithms aren't overly complicated to implement..
Conceptually, estc has the distribution and mindshare to properly rearchitect but seems like potl misexecution as they focus on observability and security vs. Core search that they're missing the ball here for core search customers
Interesting thread. They're talking that Elastic hasn't automatically switched on vector search. This seems to be as Elastic allows the client to plug in their own NLP model. However, it seems very easy to do this reading in the Elastic docs. https://www.elastic.co/blog/how-to-deploy-nlp-text-embeddings-and-vector-search
What are your thoughts on how they're falling behind in vector search?
What's the source that they're falling behind? If this is the case, imo Elastic should be able to catch up, as AI algorithms aren't overly complicated to implement..
Conceptually, estc has the distribution and mindshare to properly rearchitect but seems like potl misexecution as they focus on observability and security vs. Core search that they're missing the ball here for core search customers
No source. Think its a nascent but growing commentary amongst devs re: elastic search and their product roadmap falling behind in vector search vs New startups like weaviate. E.g. take this reddit thread: https://www.reddit.com/r/elasticsearch/comments/11v6arf/does_elasticsearch_use_vector_search_by_default
Interesting thread. They're talking that Elastic hasn't automatically switched on vector search. This seems to be as Elastic allows the client to plug in their own NLP model. However, it seems very easy to do this reading in the Elastic docs. https://www.elastic.co/blog/how-to-deploy-nlp-text-embeddings-and-vector-search