Is Hadoop truly dead, or does it still have a place in the modern Big Data ecosystem?

All answers to this question.

Hadoop as a "brand" is fading, but its' core components are still alive. MapReduce is mostly dead—replaced by Spark—but HDFS is still incredibly efficient for high-throughput, on-prem storage. The main reason companies move away from Hadoop isn't performance; it's the massive operational cost of managing the hardware and the complex configuration. Cloud-native storage (S3/ADLS) decoupled from compute is simply more flexible and cost-effective for most. However, if you have massive datasets (Petabytes) and already own the hardware, staying on-prem with a modernized Hadoop stack can actually be cheaper than paying the "cloud tax" on egress fees.

   Answered 2024-05-24 by Susan White

What about the security aspect? Many of our government clients refuse to move to the cloud due to perceived risks. Is there a "Cloud-Native On-Prem" solution that offers the best of both worlds?

   Answered 2024-05-28 by Richard Harris

• Richard, we looked into "MinIO" which provides an S3-compatible API but runs on your own hardware. It allowed us to keep our data on-prem while using modern cloud-native tools like Presto and Trino for querying. This gave us the "modern" feel without the security concerns of the public cloud. We basically replaced HDFS with MinIO and kept our compute layer flexible. It's a great middle-ground for highly regulated industries.

     Commented 2024-06-01 by William King

The talent pool is another factor. Finding a good Hadoop admin is getting harder every day, whereas everyone knows how to manage S3 or Snowflake.

   Answered 2024-06-05 by Linda Garcia

• Exactly, Linda. The "brain drain" from the Hadoop ecosystem is the real reason it feels like it's dying. Most new engineers don't want to learn how to tune YARN parameters when they can just click a button in the cloud.

     Commented 2024-06-07 by Brian Anderson