Scale By The Bay 2019: Evan Chan, Rust and Scala, Sitting in a Tree….

As a Scala developer of many years, I started getting into Rust out of frustration with Scala and the JVM, working on in-memory databases and high performance data manipulation code. Rust appealed due to its promise of safety, performance, AND high level abstractions. Does it really deliver, and how does it compare with Scala in those respects? In particular:
Safety: what does it mean to be a safe language by default? Let’s compare the two languages approach to safety
What are some similar and dissimilar functional features?
Performance: A close look at how Rust delivers fast performance without sacrificing FP, or: Rust vs Scala functional transforms
Why Rust holds huge promise in data engineering
Is it possible to take advantage of some Rust while keeping your Scala codebase intact?

Evan Chan
Senior Software Engineer
USA
Websitetwitter.com/evanfchan
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Evan loves to design, build, and improve bleeding edge distributed data and backend systems using the latest in open source technologies. He is the creator of the FiloDB open-source distributed time-series database, as well as the Spark Job Server. He has led the design and implementation of multiple big data platforms based on Storm, Spark, Kafka, Cassandra, and Scala/Akka, including a columnar real-time distributed query engine. He has been an active contributor to the Apache Spark project, and a two-time Datastax Cassandra MVP. He has built Spark applications since Spark 0.8, Cassandra since 0.6. He is a big believer in GitHub, open source, and meetups, and have given talks at various conferences including Strata, Spark Summit, Cassandra Summit, FOSS4G, and Scala Days. He has a Bachelors and Masters of Electrical Engineering, with distinction, from Stanford University. In his spare time he is a family man, photographer, foodie, avid Oakland Athletics fan, and committed follower of Jesus.

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