In 2025, agentic AI technology dominated the data management landscape, heavily influenced by the Model Context Protocol (MCP), semantic modeling, and PostgreSQL database support. Data management vendors recognized the necessity of MCP to securely connect agents with data sources, enhancing development frameworks and reducing failure rates in AI projects to combat common challenges like data inconsistency, lack of talent, and high costs. Furthermore, the importance of semantic layers surged, helping standardize metadata for better data integration. Major acquisitions, such as Databricks and Snowflake’s ventures into PostgreSQL databases, reflected a growing trend to leverage advanced database capabilities for AI applications. Amid reduced funding, consolidation emerged as a significant trend, with tech giants acquiring independent vendors to create comprehensive data ecosystems. As businesses desire end-to-end solutions, these changes signal a shift towards unified platforms, emphasizing the rising necessity for robust, integrated data management strategies essential for successful AI deployment.
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