Vector Database Stories
From company news to technical tutorials – explore the most popular content on the Zilliz blog.
Exploring Multimodal Embeddings with FiftyOne and Milvus
Exploring how multimodal embeddings work with Voxel51 and Milvus.
Introduction to LangChain
A guide to LangChain, including its definition, workflow, benefits, use cases, and available resources to get started.
Building Zilliz Cloud in 18 Months: Lessons Learned While Creating a Scalable Vector Search Service on the Public Cloud
Discover the insights gained and challenges overcome during the 18-month journey of creating Zilliz Cloud, a scalable cloud service built from open-source.
Evaluating Your Embedding Model
In this blog, we'll review some key considerations for selecting a model. We'll also review a practical example of using Arize Pheonix and RAGAS to evaluate different text embedding models.
TL;DR Milvus Regression in LangChain v0.1.5
If you are encountering a "KeyError: 'pk'" error when using Langchain v0.1.5 to connect to Milvus, it is due to a recent Milvus regression not automatically generating "pk" field (primary key) values.
Zilliz Cloud Pipelines February Release - 3rd Party Embedding Models and Usability Improvements!
The latest updates to Zilliz Cloud Pipelines in February focuses on new embedding models and ease of use.
Zilliz Joins the AI Alliance: Advancing Open Innovation in AI for a Better Future
Zilliz is proud to join the AI Alliance, a consortium that fosters open innovation and responsible AI development.
Introducing the Databricks Connector, a Well-Lit Solution to Streamline Unstructured Data Migration and Transformation
The latest release of Zilliz Cloud introduces a Databricks Connector, a well-lit solution to streamline this process by integrating Apache Spark/Databricks and Milvus/Zilliz Cloud.
The High-performance Vector Database Zilliz Cloud Now Available on Google Cloud Marketplace
With Zilliz Cloud available on GCP Marketplace, you can use Google Cloud's infrastructure and resources with simplified payment methods.