Standard_E4ds_v5 on Databricks
Standard_E4ds_v5 is a memory optimized Azure worker type with 4 vCPUs and 32 GB of memory. On Databricks it uses 1.5 DBUs an hour, so 1 node on Jobs Compute in East US costs $0.738 an hour: $0.45 for the DBUs and $0.288 to Azure for the machine.
Azure · Memory optimized · Edsv5
Standard_E4ds_v5 at a glance
- vCPUs
- 4
- Memory
- 32 GB
- Own SSD
- 150 GB
- DBUs an hour
- 1.5
- Classic compute
- With Photon
- 3.75
- DBUs an hour, Jobs Compute
- 1 node an hour
- $0.738
- Jobs Compute, East US
1 node an hour on each kind of compute
In East US on the Premium plan. Databricks charges the DBUs, Azure the machine. A cluster pays this for every worker and for the driver.
| Compute | DBUs an hour | A DBU | Databricks | Machine | An hour |
|---|---|---|---|---|---|
| Jobs Compute | 1.5 | $0.30 | $0.45 | $0.288 | $0.738 |
| Jobs Compute + Photon | 3.75 | $0.30 | $1.13 | $0.288 | $1.41 |
| All-Purpose Compute | 1.5 | $0.55 | $0.825 | $0.288 | $1.11 |
| All-Purpose Compute + Photon | 3 | $0.55 | $1.65 | $0.288 | $1.94 |
| Lakeflow pipelines Core | 1.5 | $0.30 | $0.45 | $0.288 | $0.738 |
| Lakeflow pipelines Pro | 1.5 | $0.38 | $0.57 | $0.288 | $0.858 |
| Lakeflow pipelines Advanced | 1.5 | $0.54 | $0.81 | $0.288 | $1.10 |
In each region
1 node an hour on Jobs Compute, Premium, cheapest first.
| Region | Machine | An hour |
|---|---|---|
| East US | $0.288 | $0.738 |
| East US 2 | $0.288 | $0.738 |
| West US 2 | $0.288 | $0.738 |
| West US 3 | $0.288 | $0.738 |
| Central India | $0.302 | $0.752 |
| Sweden Central | $0.304 | $0.754 |
| Canada Central | $0.316 | $0.766 |
| North Europe | $0.32 | $0.77 |
| Central US | $0.325 | $0.775 |
| UK South | $0.338 | $0.788 |
| France Central | $0.338 | $0.788 |
| West Europe | $0.346 | $0.796 |
| Germany West Central | $0.346 | $0.796 |
| Southeast Asia | $0.348 | $0.798 |
| Japan East | $0.348 | $0.798 |
| Australia East | $0.348 | $0.798 |
| Brazil South | $0.456 | $0.906 |
Other memory optimized sizes
- Standard_E4ds_v54 vCPUs, 32 GB, 1.5 DBUs an hour
- Standard_E8ds_v58 vCPUs, 64 GB, 2.75 DBUs an hour
- Standard_E16ds_v516 vCPUs, 128 GB, 5.5 DBUs an hour
- Standard_E32ds_v532 vCPUs, 256 GB, 11 DBUs an hour
- Standard_E48ds_v548 vCPUs, 384 GB, 16.5 DBUs an hour
- Standard_E64ds_v564 vCPUs, 512 GB, 22 DBUs an hour
- Standard_E96ds_v596 vCPUs, 672 GB, 33 DBUs an hour
Questions
- How many DBUs does Standard_E4ds_v5 use on Databricks?
- Standard_E4ds_v5 uses 1.5 DBUs an hour on Databricks classic compute without Photon. With Photon it uses 3.75 DBUs an hour on Jobs Compute and 3 on All-Purpose Compute, as Databricks' price list gives them.
- How much does Standard_E4ds_v5 cost an hour on Databricks?
- In East US, 1 Standard_E4ds_v5 node on Jobs Compute costs $0.738 an hour: $0.45 to Databricks for 1.5 DBUs at $0.30 each, and $0.288 to Azure for the machine. On All-Purpose Compute the same node costs $1.11 an hour, and on Lakeflow pipelines Core $0.738. A cluster pays this for every worker and for the driver.
- Does Photon cost more on Standard_E4ds_v5?
- Yes, by the hour: with Photon, 1 Standard_E4ds_v5 node on Jobs Compute in East US costs $1.41 an hour instead of $0.738, because it uses 3.75 DBUs an hour instead of 1.5. It saves money only when the job finishes fast enough to make up the difference.
- Which region is cheapest for Standard_E4ds_v5 on Databricks?
- East US, at $0.738 an hour for 1 node on Jobs Compute, against $0.906 in Brazil South, the dearest of the 17 regions listed here that offer it. Databricks charges the same for a DBU of Jobs Compute in every Azure region listed, so the gap is the machine.
- What is the same size as Standard_E4ds_v5 on the other clouds?
- The nearest worker types of the same kind are r6id.xlarge on AWS and n2-highmem-4 on Google Cloud. Each cloud gives its own DBUs an hour for its types, so compare what a cluster costs in the calculator, not the DBUs alone.
- What is the next size up from Standard_E4ds_v5?
- Standard_E4ds_v5 is the smallest size of its family listed here. One size up is Standard_E8ds_v5, at 2.75 DBUs an hour.
Sources