Apache Hadoop vs Apache Spark

Hadoop vs Spark

Both are big data frameworks, but Spark is generally much faster. They're often used together.

Comparison

Aspect	Hadoop	Spark
Processing	Disk (MapReduce)	In-memory
Speed	Slower	Up to 100x faster
Real-time	No (batch)	Yes (streaming)
Storage	HDFS built-in	Uses external (HDFS, S3)

Hadoop's Strengths

• Cheap, reliable storage (HDFS).
• Great for huge batch jobs where speed isn't critical.

Spark's Strengths

• In-memory = blazing fast.
• Handles batch, streaming, ML, and SQL.
• Easier APIs (Python, Scala, Java).

Used Together

Common setup: store data in Hadoop HDFS, process it with Spark for speed.

FAQs

Is Hadoop dead?

No — HDFS storage is still widely used, even if Spark replaced MapReduce for processing. More in our Big Data guides.

Which should I learn?

Spark — it's faster, more versatile, and in higher demand.