Apache Druid 29.0, an open-source distributed database for real-time analytics, introduces enhancements in performance, ecosystem integration, and SQL standard compliance. The latest release supports numerical columns for EARLIEST/LATEST aggregators during data ingestion, improving data modeling for queries. The multi-stage query engine now includes broader cloud support, allowing Azure and GCP blob storage for fault tolerance and enabling CSV export to S3. SQL capabilities have expanded with PIVOT/UNPIVOT and unequal joins, while window functions have seen improvements. Druid 29.0 also features new extensions like Spectator Histogram and DDSketch, the latter offering better accuracy at quantile ends. Additionally, Druid can now ingest system field information, such as parquet partition folder names, and supports data sourcing from Deltalake, easing integration with existing data platforms. The release is part of a broader effort to boost performance, enhance compatibility with cloud ecosystems, and align with SQL standards, encouraging user feedback through community channels.