Post by Sonal Holankar

#InterestingBigDataEngineering 😊 🚨 Databricks Free Edition – What I Discovered (Hands-On!) 🚨 I recently spent some time exploring the Databricks Free Edition workspace, and here are a few practical limitations I encountered while working on real use cases 👇 🔍 Key Observations: 1️⃣ Scala + Serverless = Not Yet Supported If you're planning to use Scala, Serverless compute won’t work (at least for now). You’ll need to switch to a classic cluster that supports Scala. 2️⃣ PySpark RDDs Not Allowed Tried working with RDDs on Serverless compute — no luck ❌ Looks like Databricks is pushing more toward DataFrame-based APIs. 3️⃣ PERSIST TABLE Not Supported Attempted to persist tables using SQL… but Serverless compute doesn’t support it yet. 📸 I’ve attached screenshots below for reference so you can see exactly what errors/limitations look like in practice. 💡 My Takeaway: Serverless is great for quick setups and ease of use, but if you're doing advanced operations or using Scala/RDDs, classic clusters are still essential. #Reference : https://lnkd.in/exyCrHns 🤔 Curious to hear from you: Have you faced any other limitations in Databricks Free Edition? Or found workarounds for these? Drop your thoughts in the comments 👇 #Databricks #BigData #DataEngineering #PySpark #Scala #CloudComputing