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Explore the revolutionary approach of rewriting big data systems in Rust through this 34-minute conference talk that examines the benefits and challenges of migrating from traditional big data technologies to Rust-based implementations. Learn from ASF Member and Apache OpenDAL PMC Chair Hao Ding, who brings extensive experience as a Database Engineer at Databend Labs, as he discusses the motivations behind choosing Rust for big data applications, including its memory safety guarantees, performance characteristics, and concurrency model. Discover practical insights into the migration process, architectural considerations, and real-world examples of successful Rust implementations in the big data ecosystem. Gain understanding of how Rust's ownership model and zero-cost abstractions can address common pain points in big data processing, such as memory management overhead and system reliability. Examine case studies and performance comparisons that demonstrate the potential advantages of Rust over traditional languages like Java and Scala in big data contexts, while also addressing the challenges and trade-offs involved in such migrations.
