Manual sharding pains, A look inside Milvus’s distributed architecture, and Milvus MCP Server
"There are a lot of opportunities to build agent based applications"
? Manual Sharding is a Bad Idea for Vector Databases
“Sharding manually felt like stepping into the stone age. No company should have to endure that.” - Alex, CTO of an enterprise AI SaaS startup?
Our VP of Engineering explores the scaling challenges of pgvector and similar databases that rely on manual sharding. The article explains why this approach leads to resource waste and engineering bottlenecks, then highlights how Milvus's segment-based architecture eliminates these problems with automated scaling and dynamic load balancing.
An AI SaaS startup originally built their semantic search on pgvector, but switched to Milvus. At 100 million vector embeddings, query latency spiked to over a second, far beyond what customers would tolerate.
??Day in the Life of a Milvus Datum
Let’s take a stroll in a day of the life of Dave, the Milvus datum! Follow Dave through Milvus's distributed architecture, demystifying how data moves across proxy nodes, message queues, and storage layers. Learn how this carefully designed system efficiently handles billions of vectors while maintaining sub-100ms query performance at scale.?
?? Understand the design of Milvus Distributed at a high-level, including concepts like data nodes, index nodes, shards, partitions, and segments.
?? Make more informed deployment decisions and debug corner-case performance issues.
??♂? More generally, become a Milvus hero who is able to scale to billions of vectors with ease!
Read more: A Day in the Life of a Milvus Datum?
??How to Use Anthropic MCP Server with Milvus
Riding the MCP hype wave? This guide shows how Model Context Protocol creates a universal data pipeline for AI agents while Milvus powers the vector search behind the scenes. Connect your Milvus Database via MCP Server to Claude or Cursor. It helps you interact with your Milvus Database through:
? ???????? ???????? ???????????? - Search for Documents using text
? ???????? ???????????????????? - Insert / Upsert or Delete data
? ???????????????????? ???????????????????? - List / Create and get some information about your collections
? ?????????? ???????????????????? - Create Indexes on the fly
Get Started: How to Use Anthropic MCP Server with Milvus
??? PODCAST: Structured Output with Outlines
?? NEW PODCAST EPISODE with Cameron Pfiffer from .txt and Stefan Webb ?? They discuss the intersection of generative AI, developer advocacy, and structured output. Cameron shares his journey into the field, the mission of .txt, and the importance of constrained sampling in AI development. The conversation explores the functionalities of Outlines, a tool designed to enhance structured output, and its future developments. Additionally, they discuss the integration of vector databases with constrained output and how listeners can engage with the community and resources available.
??? Listen: https://creators.spotify.com/pod/show/chloe-williams8/episodes/Structured-Output-with-Outlines-e304v4o
Upcoming Events
March 27: Milvus Hybrid Search: Combining Keyword Precision with Semantic Power for Next-Gen Data Retrieval (virtual)
This webinar demonstrates a unified approach to document retrieval by combining advanced web crawling with a hybrid search architecture that leverages both full text and dense vector search within Milvus. Learn how Crawl4AI is used to extract documentation which is then ingested into Milvus. Topics covered:?
April 3: Smarter RAG Pipelines: Scaling Search with Milvus and Feast (virtual)
Join us for a deep dive into building smarter Retrieval-Augmented Generation (RAG) pipelines using Milvus and Feast with Francisco Javier Arceo . Learn how to integrate these open source tools to scale vector search, manage dynamic metadata, and optimize retrieval. We'll demonstrate how to combine Feast’s feature store with Milvus’s high-dimensional similarity search to ensure your RAG system retrieves the most relevant data at inference time.
April 10: Zilliz Cloud Product Demo (virtual)
Join our monthly demo for a technical overview of Zilliz Cloud, a highly scalable and performant vector database service for AI applications
This webinar is an excellent opportunity for developers to learn about Zilliz Cloud's capabilities and how it can support their AI projects. Register now to join our community and stay up-to-date with the latest vector database technology.