Databricks is acquiring Mooncake, an early-stage startup focused on bridging PostgreSQL with lakehouse formats, to eliminate the need for ETL pipelines entirely. Financial terms of the deal are not being publicly disclosed. The technology promises to make operational data instantly available for analytics and AI workloads, with performance improvements ranging from 10x to 100x faster for common data movement operations. Nikita Shamgunov, who joined Databricks as VP of Engineering after leading Neon, told Databricks co-founder and chief architect Reynold Xin that Databricks should buy Mooncake on his literal first day at the company. Mooncake has several technologies in its portfolio. There is the ‘pgmooncake’ extension that enables analytical workloads to run on PostgreSQL. Then there is the moonlink component that Shamgunov describes as an acceleration tier. It enables real-time transformation between row-oriented PostgreSQL data and columnar analytical formats without traditional ETL pipelines. “Moonlink allows you to basically create a mirror of your OLTP data in a columnar representation in Iceberg and Delta,” Shamgunov explained. “Moonlink also supports an acceleration tier as well. So in many places, you accumulate latencies when you query the data lake by metadata lookups, or s3 both on the way in and on the way out.”