Community
Relational Databases vs Vector Databases
Choosing the right database is crucial. Relational databases manage structured data well, while vector databases excel in unstructured data and AI tasks. However, before adding a vector database it's important to evaluate whether the benefits outweigh the costs.
Case Study
Creating Personalized User Experiences through Vector Databases
Explore how vector databases enhance personalized user experiences
Case Study
The Role of Vector Databases in Predictive Analytics
Explore how vector databases enhance Predictive Models and their applications.
Engineering
Understanding Faiss (Facebook AI Similarity Search)
Faiss (Facebook AI similarity search) is an open-source library for efficient similarity search of unstructured data and clustering of dense vectors.
Introduction to LangChain
A guide to LangChain, including its definition, workflow, benefits, use cases, and available resources to get started.
Engineering
Build AI Apps with Retrieval Augmented Generation (RAG)
A comprehensive guide to Retrieval Augmented Generation (RAG), including its definition, workflow, benefits, use cases, and challenges.
Engineering
An Introduction to Natural Language Processing
Learn the intricacies of Natural Language Processing and how vector databases, like Zilliz Cloud, transform NLP with efficient embedding storage and retrieval.
Product
How to Choose A Vector Database: Elastic Cloud vs. Zilliz Cloud
Compare Elastic Cloud vs. Zilliz Cloud in this in-depth benchmark, cost and features comparison.
Product
What's New in Milvus version 2.2.9
Look what the team added in the latest Milvus release! Dynamic Schema, JSON support, RBAC, and more!