Fast and scalable data transfer is crucial in today's decentralized data ecosystems and data-driven applications, including extraction-transformation-loading (ETL) pipelines, and data science workflows. Transfers often occur across heterogeneous environments—ranging from cloud-hosted systems to local consumer devices—with varying compute and network constraints. However, existing solutions struggle to balance performance with generality across such diverse setups. We recently proposed XDBC, a holistic data transfer framework that decomposes the pipeline into logical components with multiple physical implementations per component. Its modular architecture enables seamless system integration and automatic tuning based on workload and environment characteristics. In this demonstration, we present Enter the Warp, an interactive game built around XDBC that visualizes data transfer as a space mission. Players configure transfer parameters, monitor live throughput metrics, and optimize performance to shield Earth from meteor strikes, gaining an understanding and hands-on experience of data transfer challenges in an engaging and intuitive way.

Data are naturally produced at different locations and hence stored on different DBMSes. To maximize the value of the collected data, today's users combine data from different sources. Research in data integration has proposed the Mediator-Wrapper (MW) architecture to enable ad-hoc querying processing over multiple sources. The MW approach is desirable for users, as they do not need to deal with heterogeneous data sources. However, from a query processing perspective, the MW approach is inefficient: First, one needs to provision the mediating execution engine with resources. Second, during query processing, data gets "centralized" within the mediating engine, which causes redundant data movement. Recently, we proposed in-situ cross-database query processing , a paradigm for federated query processing without a mediating engine. Our approach optimizes runtime performance and reduces data movement by leveraging existing systems, eliminating the need for an additional federated query engine. In this demonstration, we showcase XDB, our prototype for in-situ cross-database query processing. We demonstrate several aspects of XDB, i.e. the cross-database environment, our optimization techniques, and its decentralized execution phase.