Weaviate distinguishes itself with comprehensive integrations and an open-source approach, achieving 15,926 GitHub stars and 338,540 weekly npm downloads, emphasizing scalability in AI-native applications. Milvus, with 44,012 GitHub stars, excels in high-performance semantic similarity searches and scaling to billions of vectors, demonstrating its strength in large-scale, robust AI solutions.
Best for
Weaviate is the better choice when teams seek robust AI-native application development with strong integrations across multiple platforms, particularly for projects requiring open-source flexibility and scalability.
Best for
Milvus is the better choice when working with extensive datasets demanding high-performance semantic search capabilities and when prototyping with ease is essential due to its seamless deployment options.
Key Differences
Verdict
Weaviate is ideal for teams focusing on AI-native applications with strong open-source values and broad language support. In contrast, Milvus is preferred for companies handling massive vector datasets seeking high-performance search capabilities. Choose Weaviate for diverse AI agent integration and use Milvus if semantic search and scalability for large vectors are critical.
Weaviate
Bring AI-native applications to life with less hallucination, data leakage, and vendor lock-in
Weaviate is praised for its robust AI capabilities and ease of integration, often achieving high ratings ranging from 4 to 5 stars on platforms like G2. Users appreciate its open-source nature and ability to handle complex AI tasks efficiently, as noted in various social mentions on forums like Reddit and Hacker News. However, some users reference challenges with controlling AI functions, tracking costs, and debugging when running AI agents. The pricing sentiment is generally positive, with a focus on its value for open-source projects, contributing to an overall strong reputation in the AI tools market.
Milvus
Plays nicely with all your favorite AI dev tools
Milvus is praised for its high-performance semantic similarity searches and effective integration with vector databases, receiving consistently high ratings on review platforms like G2. Users highlight its strong capabilities and recent enhancements, such as built-in full-text search and improved scalability, as major strengths. Social mentions emphasize Milvus's role in enhancing AI applications, from semantic search to language model optimization, indicating satisfaction with its robust features and performance improvements. The sentiment on pricing is generally positive as updates focus on reducing costs and improving efficiency, contributing to its overall strong reputation in the industry.
Weaviate
Stable week-over-weekMilvus
Stable week-over-weekWeaviate
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Pricing found: $45 /mo, $400 /mo, $45 / month, $400 / month, $0.01668 / 1m
Milvus
Weaviate (10)
Milvus (2)
Only in Weaviate (10)
Only in Milvus (10)
Shared (5)
Only in Weaviate (15)
Only in Milvus (15)
Weaviate
What do you like best about Weaviate?Weaviate stores the data objects as vectors in multidimensional space, so you can search and find relationships between the data based on semantic meaning, resulting in great and stable accuracy. Their customer support is impeccable, and there's a great community environment too in Slack. Review collected by and hosted on G2.com.What do you dislike about Weaviate?Could focus more on AI docs for direct API access. Review collected by and hosted on G2.com.
What do you like best about Weaviate?The tech support is fantastic: ticket ownership, fast turn-around times, professional, personable, and proactively willing share product knowledge with the end user to better help them understand the Weaviate product. Thank you. Review collected by and hosted on G2.com.What do you dislike about Weaviate?Nothing. We had one issue with our serverless cloud and Weaviate support assigned four engineers to quickly resolve the issue. Review collected by and hosted on G2.com.
What do you like best about Weaviate?Weaviate was so easy to integrate and use. The documentation is easy to follow, the Weaviate AI is super helpful for navigating common problems, and their customer support is next level! Facing a challenge is somehow a pleasant experience - you get a swift response and an expert perspective on your problem. Review collected by and hosted on G2.com.What do you dislike about Weaviate?It would've been great to have PHP instructions in the docs, or just simple HTTP requests. Review collected by and hosted on G2.com.
Milvus
What do you like best about Milvus?Highlight for Omnichannel, all modes of service in a single tool. Real-time monitoring of terminals. SLA management, reports, and dashboards. Knowledge base with self-service for end users. Review collected by and hosted on G2.com.What do you dislike about Milvus?Configuration complexity for smaller companies, with a wide range of functionalities. Structure more oriented towards the IT sector. Cloud-based platform, any instability interrupts access. Review collected by and hosted on G2.com.
What do you like best about Milvus?Native architecture for vectorsSpecifically designed for large-scale vector storage and search, unlike traditional databases that are adapted.Efficient support for dense and sparse embeddings, essential for modern AI models. Review collected by and hosted on G2.com.What do you dislike about Milvus?Operational and deployment complexityIntricate distributed architecture: Multiple components (coordinators, workers, etc.) require separate configuration and monitoring.Heavy infrastructure dependency: Need for Kubernetes or container orchestration for production deployment.Limited standalone version: The "standalone" version is not suitable for production, only for testing. Review collected by and hosted on G2.com.
What do you like best about Milvus?Milvus stands proud as an outstanding open-source vector database for its effective guide for similarity seek and AI programs. What I like satisfactory approximately Milvus is its distinctly efficient and scalable architecture, which seamlessly handles massive-scale datasets with millions or even billions of vectors Review collected by and hosted on G2.com.What do you dislike about Milvus?One major drawback is its quite steep learning curve, especially for users new to vector database and AI applications Review collected by and hosted on G2.com.
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Data Agents with Shreya Shankar - Weaviate Podcast #135!
Apr 6, 2026
OCR vs. Image Embeddings for PDF RAG: Which One is Better?
Mar 30, 2026
Late Interaction combines the best of Keyword and Semantic Search
Mar 24, 2026
Multi-Vector Search with Amélie Chatelain and Antoine Chaffin - Weaviate Podcast #134!
Mar 23, 2026
Milvus
No YouTube channel
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Show HN: Open-sourced AI Agent runtime (YAML-first)
Been running AI agents in production for a while and kept running into the same issues:<p>controlling what they can do tracking costs debugging failures making it safe for real workloads<p>So we built AgentRuntime, the infrastructure layer we wished we had. Not an agent framework, but the platform a
Milvus
Build a #GraphRAG Agent with @neo4j and #Milvus 📈 🤖 This tutorial combines the strengths of graph databases and vector search and creates an agent to provide accurate and relevant answers to user
Build a #GraphRAG Agent with @neo4j and #Milvus 📈 🤖 This tutorial combines the strengths of graph databases and vector search and creates an agent to provide accurate and relevant answers to user queries. 💪 🔗 https://t.co/mFtZL9Nutq #Vectordatabase #Milvus #RAG https://t.co/pMk0yrgqv2
Shared (1)
Only in Weaviate (4)
Only in Milvus (4)
For smart contextual search across unstructured data, Weaviate may be superior due to its specific personalization agent features, while Milvus would excel in projects requiring strong semantic searching capabilities.
Weaviate offers a combination of usage-based and tiered pricing with a free tier, highlighting cost-effective scaling for modular projects, whereas Milvus provides tiered pricing, focusing on efficient scaling for large data.
Milvus has notable community support with 44,012 GitHub stars indicating a larger user and contributor base compared to Weaviate's 15,926, potentially providing faster feedback and more community-driven improvements.
Yes, integrating both tools can be beneficial for leveraging Weaviate's AI-native application capabilities alongside Milvus's robust semantic search for comprehensive data solutions.
Milvus may be easier to get started with, especially for prototyping, due to its VectorDB-as-a-library feature that allows it to run with a simple pip install in notebooks and laptops.
