AI Searching across multiple languages Discover how easy it can be to implement advanced multilingual search and give your users the seamless, relevant results they deserve—regardless of language.
State of search What is federated search? Learn what federated search is and the use cases it unlocks.
State of search Choosing the best model for semantic search A comparison of model performance, cost, and relevancy in regard to building semantic search.
State of search Meilisearch vs Algolia A comparison between the key features of Meilisearch and Algolia.
State of search Full-text search vs vector search A comparative analysis of full-text search, vector search, and hybrid search.
State of search What are vector embeddings? In machine learning and AI, vector embeddings are a way to represent complex data, such as words, sentences, or even images as points in a vector space, using vectors of real numbers.
State of search What is a vector database? Vector databases are specialized systems to store, manage, and query data in the form of vector embeddings. They are optimized for similarity search, which involves finding the most similar items to a given query vector.
State of search Meilisearch vs Typesense Comparing the key features between open-source search engines Meilisearch and Typesense.
State of search How to deliver the best search results: inside a full text search engine Through an exploration of Meilisearch's inner workings, we'll uncover how modern search engines deliver accurate results at the speed of your keystrokes.
State of search When does Postgres stop being good enough for full text search? An overview of nine areas where Postgres full text search falls short compared to search-focused databases.
