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Databricks set to accelerate agentic AI by up to 100x with ‘Mooncake’ technology — no ETL pipelines for analytics and AI
Enterprises often use expensive ETL pipelines to move PostgreSQL operational data for analytics or AI, causing delays and requiring dedicated engineering teams. This traditional approach is insufficient for the rapid pace of AI agent-driven application development. Databricks is acquiring Mooncake to eliminate ETL pipelines by making operational data instantly available for analytics and AI. Mooncake's technology allows analytical workloads to run directly on PostgreSQL and provides real-time transformation to columnar formats without traditional ETL. This integration is expected to improve data movement performance by 10x to 100x. The urgency of this acquisition is highlighted by the increasing number of databases created by AI agents. Mooncake's approach simplifies data access for agents, enabling faster iteration. Databricks' strategy positions it against cloud providers' managed PostgreSQL offerings like Google's AlloyDB and Amazon's Aurora, emphasizing integrated operational and analytical models. This acquisition aims to free up engineering resources by simplifying data infrastructure management and enabling faster deployment of AI-driven applications. Ultimately, this allows development teams to access operational data for analytics and AI without data engineering bottlenecks.
