What are the disadvantages of Apache Spark?

Apache Spark’s primary disadvantages include its high memory consumption, as it relies heavily on in-memory computing, which can lead to resource contention on underpowered hardware. It can also be complex to learn for beginners, as it requires knowledge of distributed computing concepts. Additionally, Spark’s performance may lag for small datasets, where simpler tools like Pandas or SQLite might be more efficient.