AI Ecosystem
Singdata Lakehouse is deeply integrated with mainstream AI development frameworks and workflow platforms, providing vector storage, full-text search, file storage, and data query capabilities as the data infrastructure for AI applications.
Contents
| Integration | Description |
|---|---|
| Dify Integration | Use Lakehouse as Dify's vector database and file storage service, supporting RAG knowledge base construction and unstructured data management |
| N8N Integration | Use Lakehouse nodes in N8N visual workflows, supporting data queries, table data comparison, and multi-database workflow automation |
| LangChain Integration | LangChain Singdata plugin that brings Lakehouse capabilities into LangChain AI applications, supporting vector retrieval and RAG application development |
| Unstructured Data ETL Pipeline | Use Unstructured to convert PDFs, emails, images, and other unstructured data into JSON, write it to Lakehouse, and build a vector index to feed RAG applications |
| Datus Data Engineering Agent | An open-source data engineering agent that provides domain-aware intelligent assistance for analysts and business users, integrating with Lakehouse via MCP Server |
Quick Selection Guide
I'm building an AI application with Dify and need knowledge base storage → Dify Integration: configure Lakehouse as a vector database or file storage
I'm building an automated workflow with N8N and need to operate a database → N8N Integration: install the Lakehouse N8N node, supporting queries and data comparison
I'm developing an AI application with LangChain and need vector retrieval → LangChain Integration: use the LangChain Singdata plugin to connect to Lakehouse
I have large volumes of PDFs, images, and other unstructured files and need to build RAG → Unstructured Data ETL Pipeline: complete pipeline from Unstructured to a Lakehouse vector table
I want to use an AI Agent to automate data engineering tasks → Datus Integration: let the agent operate Lakehouse directly via MCP Server