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Scaling PostgreSQL to power 800M ChatGPT users

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Re: Scaling PostgreSQL to power 800M ChatGPT users

#31
post #8

Someone ask Microsoft what does it feel to be bested by an open source project on their very own cloud platform!!! Lol.

That ship sailed a long time ago, as Microsoft has offered Linux VMs in Azure for 14 years, and today, about 2/3 of VMs running there are Linux. In the public cloud era, owning the infrastructure and customer base is far more important than licenses.

Re: Scaling PostgreSQL to power 800M ChatGPT users

#33
post #26

Earlier quoted context omitted.

Are you saying this because OpenAI didnt choose SQL Server?

In 2026 is SQL Server ever the answer?

That’s kind of my point. They’re not really in competition. I bet they’d have an easier time with this scale if they were on SQL Server, but obviously that migration isn’t happening and startups don’t reach for it for many reasons.

Re: Scaling PostgreSQL to power 800M ChatGPT users

#35
> scaled up by increasing the instance size

I always wondered what kind of instance companies at that level of scalability are using. Anyone here have some ideas? How much cpu/ram? Do they use the same instance types available to everyone, or does AWS and co offer custom hardware for these big customers?

Re: Scaling PostgreSQL to power 800M ChatGPT users

#36

> scaled up by increasing the instance size I always wondered what kind of instance companies at that level of scalability are using. Anyone here have some ideas? How much cpu/ram? Do they use the same instance types available to everyone, or does AWS and co offer custom hardware for these big customers?

The major hyperscalers all offer a plethora of virtual machines SKUs that are essentially one entire two-socket box with many-core CPUs.

For example, Azure Standard_E192ibds_v6 is 96 cores with 1.8 TB of memory and 10 TB of local SSD storage with 3 million IOPS.

Past those "general purpose" VMs you get the enormous machines with 8, 16, or even 32 sockets.[1] These are almost exclusively used for SAP HANA in-memory databases or similar ERP workloads.

Azure Standard_M896ixds_24_v3 provides 896 cores, 32 TB of memory, and 185 Gbps Ethernet networking. This is generally available, but you have to allocate the quota through a support ticket and you may have to wait and/or get your finances "approved" by Microsoft. Something like this will set you back [edited] $175K per month[/edited]. (I suspect OpenAI is getting a huge effective discount.)

Personally, I'm a fan of "off label" use of the High Performance Compute (HPC) sizes[2] for database servers.

The Standard_HX176rs HPC VM size gives you 176 cores and 1.4 TB of memory. That's similar to the E-series VM above, but with a higher compute-to-memory ratio. The memory throughput is also way better because it has some HBM chips for L3 (or L4?) cache. In my benchmarks it absolutely smoked the general-purpose VMs at a similar price point.

[1] https://learn.microsoft.com/en-us/azure/virtual-machines/siz...

[2] https://learn.microsoft.com/en-us/azure/virtual-machines/siz...

Re: Scaling PostgreSQL to power 800M ChatGPT users

#37

I don’t get it. This whole thing says single writer does not scale, so we stopped writing as much and removed reads away from it, so it works ok and we decided that’s enough. I guess thats great.

This article has very little useful information...

There's nothing novel about optimizing queries, sharding and using read replicas.

Re: Scaling PostgreSQL to power 800M ChatGPT users

#38

> scaled up by increasing the instance size I always wondered what kind of instance companies at that level of scalability are using. Anyone here have some ideas? How much cpu/ram? Do they use the same instance types available to everyone, or does AWS and co offer custom hardware for these big customers?

[deleted]

Re: Scaling PostgreSQL to power 800M ChatGPT users

#39
Regarding schema changes and timeouts - while having timeouts in place is good advice, you can go further. While running the schema rollout, run a script alongside it that kills any workload conflicting with the aggressive locks the schema change is trying to take. This will greatly reduce the pain caused by lock contention, and prevent you from needing to repeatedly rerun statements on high-throughput tables.

This would be a particularly nice-to-have feature for Postgres - the option to have heavyweight locks just proactively cancel any conflicting workload. For any case where you have a high-throughput table, the damage of the heavyweight lock sitting there waiting (and blocking all new traffic) is generally much larger than just cancelling some running transactions.

Re: Scaling PostgreSQL to power 800M ChatGPT users

#40

> scaled up by increasing the instance size I always wondered what kind of instance companies at that level of scalability are using. Anyone here have some ideas? How much cpu/ram? Do they use the same instance types available to everyone, or does AWS and co offer custom hardware for these big customers?

The major hyperscalers all offer a plethora of virtual machines SKUs that are essentially one entire two-socket box with many-core CPUs. For example, Azure Standard_E192ibds_v6 is 96 cores with 1.8 TB of memory and 10 TB of local SSD storage with 3 million IOPS. Past those "general purpose" VMs you get the enormous machines with 8, 16, or even 32 sockets.[1] These are almost exclusively used for SAP HANA in-memory da…

On the AWS side there are "HANA certified" instances that max out at 1920 cores and 32 TB RAM - u7inh-32tb.480xlarge

https://docs.aws.amazon.com/sap/latest/general/sap-hana-aws-...

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