RDD vs DataFrame vs Dataset vs Parquet vs Delta Lake vs Iceberg Explained
In this video, I explain the differences between RDD, DataFrame, Dataset, Apache Parquet, Delta Lake, and Apache Iceberg in a simple and beginner-friendly way.
This comparison is designed for Data Engineers, Spark beginners, and anyone working with modern data lake and lakehouse architectures.
In this video, you will learn:
What RDD, DataFrame, and Dataset are in Apache Spark
What Apache Parquet is and why it is widely used
What Delta Lake adds on top of Parquet
What Apache Iceberg is and why it matters in multi-engine lakehouses
The key differences between processing APIs and table/storage layers
When to use each technology in real Data Engineering projects
00:04 Friendly comparison and when to use each
02:49 RDD
04:34 DataFrame
06:58 DataSet
08:42 Apache Parquet
10:25 Delta Lake
13:00 Apache Iceberg
14:28 Which one should you choose?
If you are learning Spark, ETL, lakehouse concepts, or preparing for Data Engineer interviews, this video will help you understand these technologies clearly.
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