Bridge Queries in Redpanda SQL

Redpanda SQL introduces an innovative solution for managing streaming data pipelines by addressing the common tradeoff between data freshness and file size efficiency in Iceberg lakehouses. This PostgreSQL-compatible OLAP query engine transforms Redpanda topics into queryable SQL tables, eliminating the need for ETL processes and separate analytics warehouses. A key feature, the bridge query, allows a single SQL query to seamlessly read both live records from a Redpanda topic and historical data from its corresponding Iceberg table, simplifying the process for query authors. This approach enables efficient file management by allowing larger Parquet files, which improves compression, reduces catalog overhead, and minimizes the need for constant compaction jobs. By decoupling the storage and compute processes, Redpanda SQL ensures that latency is dictated by the topic rather than the flush interval, maintaining data freshness without compromising analytics performance. This system is set to become available for self-managed Redpanda Enterprise deployments by late 2026, offering a streamlined method to manage streaming data without the complexities of dual-write systems or bolt-on compaction services.