Based on our record, Weaviate should be more popular than LangChain. It has been mentiond 38 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Undoubtedly, LangChain is the most popular framework for AI application development at the moment. The advent of LangChain has greatly simplified the construction of AI applications based on Large Language Models (LLM). If we compare an AI application to a person, the LLM would be the "brain," while LangChain acts as the "limbs" by providing various tools and abstractions. Combined, they enable the creation of AI... - Source: dev.to / about 1 year ago
Developed using Langchain and Streamlit technologies for enhanced performance. - Source: dev.to / about 1 year ago
LangChain was first released in October 2022 as an open-source side project, a framework that makes developing AI applications more flexible. It got so popular that it was promptly turned into a startup. - Source: dev.to / over 1 year ago
Being able to plug third party frameworks (Langchain, LlamaIndex) so you can build complex projects. - Source: dev.to / over 1 year ago
Alternatives to: Pinecone, Weaviate, Milvus, Azure AI Search. - Source: dev.to / 17 days ago
Explore open-source vector stores like Weaviate or Chroma if you’re still going the RAG route. - Source: dev.to / about 1 month ago
Weaviate — comes with built-in modules for semantic search. - Source: dev.to / about 1 month ago
The key difference lies in the retrieval mechanism. Vector databases focus on semantic similarity by comparing numerical embeddings, while graph databases emphasize relations between entities. Two solutions for graph databases are Neptune from Amazon and Neo4j. In a case where you need a solution that can accommodate both vector and graph, Weaviate fits the bill. - Source: dev.to / about 2 months ago
In cases where a company possesses a strong technological foundation and faces a substantial workload demanding advanced vector search capabilities, its ideal solution lies in adopting a specialized vector database. Prominent options in this domain include Chroma (having raised $20 million), Zilliz (having raised $113 million), Pinecone (having raised $138 million), Qdrant (having raised $9.8 million), Weaviate... - Source: dev.to / about 2 months ago
Haystack NLP Framework - Haystack is an open source NLP framework to build applications with Transformer models and LLMs.
Qdrant - Qdrant is a high-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Dify.AI - Open-source platform for LLMOps,Define your AI-native Apps
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
Hugging Face - The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications.
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs