The Small Container: Lightweight Compute for Multi-architecture Cloud-Edge Systems

Docker and WebAssembly (Wasm) are playing increasingly important roles in modern software development, each offering unique benefits in portability, performance, and deployment efficiency. As Wasm evolves beyond the browser into cloud-native and edge computing environments, its integration with container runtimes prompts a closer examination of performance trade-offs compared to traditional multi-platform containers. In contrast to conventional Docker containers, Wasm binaries offer a portable, compact, and secure deployment format. In this paper, we extend our prior investigation by introducing two new benchmark suites: benchx and sqlite-multiarch to explore deeper performance characteristics across Wasm and native multi-architecture containers using containerd, focusing on four platforms: AMD64, ARM64 (Nvidia’s Jetson Nano and Orin), and RISCV64 (StarFive VisionFive2). We analyze pull time, startup latency, and image size across both native and Wasm runtimes. Our results show that Wasm containers reduce image size by up to $$70\%$$ and achieve up to $$25\%$$ faster cold pull times compared to native containers. With the sqlite-multiarch benchmark, we observe Wasm startup overheads compared to native execution, which highlights both performance gaps and opportunities for runtime optimizations. Across all platforms, Wasm containers executed via containerd consistently outperformed Docker-based setups. We demonstrate that Wasm runtimes can effectively support realistic data-intensive workloads such as full-text search, JSON parsing, and R-tree spatial queries, while offering improved deployment efficiency and better performance isolation. These findings reaffirm Wasm’s potential as a complementary compute layer for heterogeneous, multi-architecture cloud-edge deployments.