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Lakehouse: Manus? MCP? Let’s Talk About Lakehouse and AI
- AI has become an unavoidable topic across various industries since the launch of ChatGPT by OpenAI in late 2022, leading many companies to transform into AI companies quickly.
- Databricks, Snowflake, and Elasticsearch have all shifted to AI data platforms or AI-ready data analytics and search products.
- The article explores the relationship between Lakehouse and AI in the data analytics domain, focusing on the Model Context Protocol (MCP) introduced by Anthropic in late 2024.
- MCP serves as a communication protocol between large models and data sources, facilitating easy interaction and collaboration.
- By integrating with MCP, tools like Claude Desktop have enhanced efficiency in working with AI data sources.
- Apache Doris MCP Server allows for direct access and exploration of data stored in Apache Doris, demonstrating the integration of AI models with data services.
- The use of a Data Lake enables seamless collaboration among different compute engines in AI development, ensuring data consistency and real-time access.
- Analytics engines like Apache Doris provide high performance and richer SQL expression capabilities, supporting complex AI scenarios with acceptable user experience.
- In the AI era, open data formats like Iceberg and data APIs play crucial roles in enabling seamless data integration and analysis for AI applications.
- Apache Doris supports both open data formats and APIs, positioning itself as a leading data analytics engine for AI applications.
- Future articles will delve into more features of Lakehouse architecture, real-time data warehouses, and query engines like Doris in supporting AI applications and data analysis.
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