Why is Java still the preferred language for Big Data and Data Engineering over Python?

All answers to this question.

Python is great for "Data Science" (exploring data, training models), but Java/Scala is for "Data Engineering" (moving and transforming data at scale). The main reason is the JVM’s multithreading capabilities and static typing. When you are processing petabytes of data across a 100-node cluster, the performance overhead of Python’s Global Interpreter Lock (GIL) and its dynamic nature becomes a massive liability. Frameworks like Apache Kafka and Flink are built in Java because they require fine-grained control over memory and concurrency. If you want to build the infrastructure that powers data, Java is your best bet.

   Answered 2024-01-07 by Nancy Turner

That’s a great debate! While Java has the performance, don’t you think PySpark and the new "Python-based" tools are closing the gap? Many developers find Java too verbose for quick data transformations. Do you think the introduction of "JStream" and better functional programming in modern Java will make it more appealing to people who currently prefer the simplicity of Python?

   Answered 2024-01-07 by George Harris

• George, even with PySpark, there's always a "serialization tax" when moving data between the Python process and the JVM. For high-throughput, low-latency pipelines, that 10-20% overhead is unacceptable. Java’s Type Safety also prevents a lot of "runtime surprises" that you only catch 4 hours into a 6-hour batch job in Python. For mission-critical data pipelines, the verbosity of Java is a small price to pay for the stability and performance it provides at scale.

     Commented 2024-01-10 by Charles King

Static typing is the unsung hero of Big Data. Being able to catch a data type mismatch at compile time saves thousands of dollars in wasted cloud compute costs.

   Answered 2024-01-12 by Sarah Green

• Sarah is 100% correct. I've seen teams lose days of work because a Python script failed halfway through a massive shuffle due to a simple type error.

     Commented 2024-01-14 by Nancy Turner