Astra DB is a high-performance NoSQL database that simplifies the process of creating vector embeddings for text chunks at the point of inserting them into the collection, allowing users to build accurate and low-latency retrieval-augmented generation (RAG) powered generative AI apps. It supports various embedding models from different providers, including OpenAI, Voyage AI, Mistral AI, Jina AI, Upstage, and NVIDIA embedding models. Astra Vectorize can create vector embeddings for text chunks at the point of inserting them into the collection, simplifying the process of ingesting data for RAG applications. The database also supports graph RAG via LangChain, which takes documents, extracts links between them, and uses those links to retrieve extra contextual information at the retrieval stage, making it easier for large language models (LLMs) to answer certain queries accurately. Astra DB's vector indexing capabilities are a combination of Cassandra's storage-attached indexing (SAI) and JVector, allowing for high throughput and accuracy even under mixed loads of reads and writes. It is available in LangChain and Langflow, which provides a visual way to build agents, making it easy to build RAG or agentic RAG within the platforms. Astra DB supports various applications, including AI resume assistants, voice agents, music recognition apps, and chatbots, and can be used with alternative vector searches like ColBERT for improved accuracy.