Big Data / Hadoop / Spark / Snowflake Servers

Big-data clusters scale by adding storage-dense nodes. The classic Hadoop HDFS DataNode is a 4U server with 12-24 LFF bays of 14-22 TB nearline drives — 200-500 TB per node. Compute (Spark executor) nodes overlap with the storage nodes in HCI-style deployments, or run separately on lighter-weight chassis.

Pro Disk Network stocks the high-density storage platforms: Dell PowerEdge R760xd2 (24× LFF, 552 TB raw with 23 TB drives), HP Apollo 4200 / 4500 series (28× LFF, optimised for Hadoop), Supermicro 4U/4N storage chassis, and the ASROCK / QCT / Quanta hyperscaler models.

For modern data-warehouse / lakehouse on-prem (Snowflake on-prem coming, Databricks, Apache Iceberg + Trino): the workload pattern shifts to NVMe-tier scratch, large memory, and 100GbE+ inter-node networking. This is more like the all-NVMe section than a classic Hadoop deployment.

Capacity planning: Hadoop HDFS replication factor 3 means 1 PB of usable storage requires 3 PB raw. With 22 TB drives at 24-bay LFF density (528 TB per node), that's 6 nodes minimum for 1 PB usable. Network: 25/100GbE between nodes, ToR leaf switches like Cisco Nexus 93180YC or Arista 7050X3.

Featured Big Data / Hadoop / Spark / Snowflake Servers

Frequently Asked Questions

What drive capacity is best for Hadoop?

14-22 TB nearline SAS/SATA at 7,200 RPM. Larger drives (22-30 TB SMR) are tempting for capacity but the per-TB seek penalty hurts MapReduce/Spark shuffle performance. Most current Hadoop deployments standardize on 14 TB or 18 TB CMR drives.

How much memory per Hadoop / Spark node?

256-768 GB depending on YARN / Spark executor sizing. Spark in particular benefits from large executor memory (32-64 GB per executor, 8-16 executors per node = 256-1024 GB total). Most modern deployments run 384-512 GB per node.

Should I use SSDs in Hadoop nodes?

For scratch / shuffle / temp directories — yes, NVMe SSD significantly speeds up Spark shuffle. For HDFS data drives — no, the cost penalty isn't worth it; sequential read on spinning rust is fine for HDFS block reads. Mix 2× NVMe (for scratch + OS) with 22× SATA HDD (for HDFS) per node.

Can I use refurbished hardware for Hadoop?

Yes — Hadoop's design assumes hardware fails. Standard practice is to add 1-2 spare drives per node, monitor SMART metrics, and let HDFS replication handle drive failures. Refurbished platforms (R740xd, DL380 Gen10) are common in production Hadoop clusters.

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