Database and compute servers.
Same work, same time.

Analytics, builds, batch jobs and databases on hardware whose speed does not depend on who else is awake. The gain is not raw power, it is repeatability.

port
1, 10, 25, 40, 100 Gbps
cores
dedicated
ecc
every machine
locations
AMS · MEP · IAD · PHX

The same work should take the same time.

Databases, analytics, build farms and batch jobs share one need: a run should take the same time as the last one. On shared hardware it does not, because another tenant's disk or CPU burst changes your timing.

A dedicated machine does not make a job faster than its hardware allows. It makes the result repeatable, and that is what lets you size capacity, compare releases and trust a benchmark.

How to choose.

  1. 01 ─ working set

    Measure the data your queries touch most. If it fits in memory, the disks are left with writes and the cold rest.

  2. 02 ─ limit

    Find out what the job waits on: CPU, memory or disk. Buy for the one that limits you.

  3. 03 ─ disks

    Choose NVMe under a database. Commit and checkpoint latency is disk latency.

  4. 04 ─ memory

    Size memory to the working set. ECC comes in every server, so only the amount is yours to pick.

  1. 01 ─

    Tail latency from a neighbour

    on a meter or a shared host

    A checkpoint or WAL write waiting behind another tenant's IO shows up as one query ten times slower than the rest.

    here

    Single tenant: the IO queue is yours alone.

  2. 02 ─

    Runs you cannot compare

    on a meter or a shared host

    On shared hardware the same job takes a different time depending on who else is busy.

    here

    Same work, same time, run after run.

  3. 03 ─

    Silent corruption

    on a meter or a shared host

    An uncorrected bit flip can damage data long before anything alerts on it.

    here

    ECC memory in every server.

What to look for in the machine.

disksNVMe under the database

Databases wait on IO latency; NVMe is where that wait gets short.

memorysized to the working set

ECC is in every server; what is left to decide is how much.

cpucores for parallel jobs

Builds and batch jobs spread across cores; more of them, shorter runs.

gpuif the job is GPU work

A GPU is available on a built-to-order machine.

The servers that fit this today are marked under the processor on the price list. The shelf changes; what to look for in the machine does not.

Does the hot set fit in memory.

Set how much data there is and how much of it is read often. Each row is a memory size we build with, around the smallest one that holds it.

the hot set against the memoryyour numbers · memory options
64 GB[no] the hot set spills to disk
128 GB[no] the hot set spills to disk
256 GB[yes] 78% taken
384 GB[yes] 52% taken
512 GB[yes] 39% taken
Hot set: 200 GB. The smallest memory size we build with that holds it is 256 GB. The operating system, connections and the database's own buffers share the same memory and are not counted here.
open this build in the configurator →

carries over: memory 256 GB

Questions to settle before ordering.

  1. 01 ─

    Can I rent a machine for one batch job?

    Yes. There is no minimum term and setup is $0. Plans renew automatically, so cancel before the renewal date; cancellation takes effect at the end of the current billing period (Terms, sections 6 and 11).

  2. 02 ─

    Can I choose Xeon or EPYC?

    On a custom build, yes: the configurator lets you pick Intel Xeon or AMD EPYC, or leave the choice to us.

The rest, for every machine: all questions and the terms.

Tell us what it serves.

The workload, the working set, where the users are. We come back with a machine sized to it, a price and a date.

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