MindsDB provides an integration with Milvus, enabling users to connect and manage vector data using SQL-like queries. This integration brings federated AI query capabilities across structured and unstructured data with Milvus as the vector database backend.
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Milvus Connectors, such as the Spark-Milvus Connector, enable seamless integration of Milvus vector databases with third-party tools like Apache Spark for machine learning and data processing workflows.
LangChain is an open-source framework that integrates with various vector databases, including Pinecone, Weaviate, and Chroma, to facilitate retrieval-augmented generation (RAG) and advanced AI workflows.
Langflow is a platform that simplifies building AI agents by connecting models, vector stores, memory, and other AI building blocks. It is relevant to vector databases as it supports integration with vector stores for AI-powered agents.
The Airbyte Milvus connector lets users sync data from various Airbyte-supported sources into Milvus as a destination, enabling low-code vector data ingestion pipelines.
The Kafka Connect Milvus Connector is a plugin for Kafka Connect that streams data into and out of Milvus, supporting real-time vector data ingestion pipelines.
The Milvus destination in Fivetran enables automated ELT pipelines that load data into Milvus as a vector database, supporting AI and similarity search workloads.
Category: Data Integration & Migration
Tags: milvus, integration, ai, sql
MindsDB provides an integration with Milvus, enabling users to connect and manage vector data using SQL-like queries. This integration brings federated AI query capabilities across structured and unstructured data with Milvus as the vector database backend.
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