Apache Spark Cluster
Indicative from-price range
Indicative from-price range for self-hosting Apache Spark Cluster on 3 servers: about $72 to $337 per month (USD), as of 2026-10-19, for the reference workload (Executor count: 4; Memory per executor (GB): 16; Concurrent Spark jobs: 2). From-price by provider, each the cheapest server in that provider's own shortlist: $72 on DigitalOcean (basic-2vcpu-4gb, 2 vCPU, 4 GB RAM, fra1); $147 on Google Cloud (e2-standard-2, 2 vCPU, 8 GB RAM, us-central1); $190 on Amazon Web Services (c9g.large, 2 vCPU, 4 GB RAM, us-east-1); $192 on OVHcloud (rise-1, 6 vCPU, 32 GB RAM, eu-west); $199 on Microsoft Azure (D2as_v7, 2 vCPU, 8 GB RAM, eastus); $199 on Hetzner (AX41, 6 vCPU, 64 GB RAM, eu-central); $787 on Servers.com (dl-01, 8 vCPU, 64 GB RAM, eu-west).
Reference workload
- Executor count: 4
- Memory per executor (GB): 16
- Concurrent Spark jobs: 2
Methodology
This range is generated automatically from public provider price lists. It has not been reviewed by a person, it is not a quote, and it may differ from the total the calculator chooses for your own workload with its AI step. Method: the calculator's offer shortlist for the reference workload (the same ranking it builds before the AI step, up to 12 offers across providers; 12 here) is priced at its monthly list price in USD. The low end is the cheapest of the per-provider from-prices below and the high end is the median server of the combined shortlist, each multiplied by 3, the smallest baseline topology (master-plus-workers). The from-price for each provider applies the same method to that provider's own shortlist (the calculator's ranking restricted to that provider), so it is the cheapest server that ranking offers there, not a recommendation. Prices are taken from the price snapshot dated 2026-10-19; prices quoted in EUR are converted with the ECB reference rate dated 2026-10-19. Servers with fewer than 2 vCPU or less than 4 GB RAM are not priced. Only server rental list prices for the product's own servers are counted: dependencies, licences, support, traffic charges, taxes and setup fees are not included.
Price sources
- Amazon Web Services: https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonEC2/current/us-east-1/index.json
- DigitalOcean: https://www.digitalocean.com/pricing/droplets
- Google Cloud: https://cloudbilling.googleapis.com/v1/services/6F81-5844-456A/skus
- Hetzner: https://www.hetzner.com/_resources/app/data/app/live_data_en_EUR.json
- Microsoft Azure: https://prices.azure.com/api/retail/prices
- OVHcloud: https://eu.api.ovh.com/1.0/order/catalog/public/eco?ovhSubsidiary=FR
- Servers.com: https://www.servers.com/products/scalable-bare-metal
Size Apache Spark Cluster for your own workloadMarkdown versionFor AI agents (llms.txt)
Apache Spark is a distributed data-processing engine that executes batch, streaming, SQL, and machine-learning workloads across a cluster of machines. It keeps intermediate data in-memory as resilient distributed datasets to avoid much of the disk I/O overhead that classic MapReduce jobs incur.
Baseline topologies
| Topology | Minimum nodes | Roles |
|---|---|---|
| master-plus-workers | 3 | spark-master, spark-worker |
| master-plus-workers-ml | 3 | spark-master, spark-worker |
What drives the cost
- Executor count
- Number of Spark executor processes across the cluster workers; each executor runs tasks in parallel up to executor_cores.
- Memory per executor (GB)
- JVM heap allocated to each executor process; the primary offer-selection driver for Spark worker sizing. Off-heap overhead adds approximately 10-20% on top of this value.
- Concurrent Spark jobs
- Number of Spark jobs expected to run simultaneously, informing driver and master scheduling capacity.
Where it runs
bare_metal, dedicated, cloud_vm
Size Apache Spark Cluster and get a cost estimate