PALO ALTO, Calif., June 10, 2025 (GLOBE NEWSWIRE) — Modern enterprises know that the future of AI and innovation hinges on real-time data, but integrating legacy operational data with low latency is a major challenge. For organizations running mission-critical workloads on Microsoft SQL Server, unlocking that data for modern platforms like Azure Databricks is often a slow, fragmented process. Traditional data integration relies on brittle batch-based pipelines and delayed ingestion cycles that cannot keep up with the demands of modern AI, real-time analytics, or dynamic decision-making. The result? A widening gap between where the data lives and where AI and Analytics value is created.