Making 768 servers look like 1

https://planetscale.com/blog/making-768-servers-look-like-1

by hisamafahri • 7 days ago

155 84 7 days ago

Load balancers, microservices and horizontal scaling?

jdw644• 7 days ago

Looks like the GIF is fully built out in code. It's really nice to look at, well made, and easy to understand too. I wonder what program or code they used. I'd love to know.

p.sI thought it was a GIF, but it's an iframe. That was a nice little surprise.

gurjeet• 7 days ago

Specifically, it's an JS-controlled/animated SVG embedded in an iframe.

jdw644• 7 days ago

Yeah, I'm looking at it in developer mode. It's using a GSAP timeline approach to update SVG properties. I'm curious how they handle security and caching for something like this. It looks like they're using Tailwind, at least. but this approach is really clean and nice.

It really feels like the best way to learn is by studying other people's code.

bddicken7• 6 days ago

Author here, thank you.

Technically, they are using js + gsap + svg embedded i the article with iframes.

Process-wise, I drafted most of them as static images in excalidraw, passed the images along to cursor for a first draft, applied styling rules, and then did a bunch of fine-tuning.

jdw644• 6 days ago

Thank you so much.!!!! It can't be easy to put this much care into helping others understand, with that hand drawn feel and everything. I really learn a lot from it. The animations were great and made everything really easy to understand. Have a nice day.!

aarvin_roshin• 7 days ago

Previously: https://news.ycombinator.com/item?id=48925420

drdexebtjl3• 7 days ago

What about sequences? The example shows an auto-incrementing user ID. How’s that possible without contention between all shards? Is the proxy responsible for sequences?

What about foreign keys? Do they all have to live on the same shard? How do you do distributed transactions?

On cross-shard reads: how do you do sorting? And cross-shard joins?

I’d love to be proven wrong, but I suspect the 768 servers look like 1 only on the very surface, and you’ll get wildly different characteristics from cross-shard and single-shard queries.

I personally would prefer if they _didn’t_ look like 1 if they can’t behave like 1.

random3• 7 days ago

A 767 servers KV store should be enough for everyone

vkazanov3• 7 days ago

Of course 768 servers NEVER behave as 1. This is physically impossible.

Global services using relational dbs typically severely restrict queries that run against the cluster. So no joins, no intervals, no grouping, etc.

Transactional queries are usually limited to something like "get a single record, preferably from cache". For many typical web services this can go VERY FAR. Only a handful of global services needs more than a few dozen database servers and a caching cluster. In fact, i have seen major businesses running off a pair of very big postgres instances.

Analytical stuff is extracted into dedicated storages optimized for throughput, like Snowflake or Redshift or BigQuery.

ahk-dev• 7 days ago

This seems like the important distinction: making the infrastructure look like one database to the application is different from making it behave like one unrestricted relational database.

At what point does hiding the sharding become counterproductive? I imagine teams still need a fairly deep understanding of shard keys, query routing, and failure modes to avoid accidentally expensive cross-shard operations.

samlambert2• 6 days ago

Transactional queries are usually limited to something like "get a single record, preferably from cache".

simply wrong

jackb40403• 7 days ago

I had this question too, even their "Database Scaling" course doesn't get to it.

https://vitess.io/docs/faq/sharding/advanced/

Looks like it's not drop-in, you need to heavily modify your data and indexes structurally to make sharding performant. Cross-shard joins are possible but need to be designed for explicitly (to be fair, indexes also need to be designed explicitly in regular SQL). IDK if a drop-in solution is possible or if this is an information-theoretical limitation.

citrin_ru• 7 days ago

The example shows an auto-incrementing user ID. How’s that possible without contention between all shards?

Why not divide ID range (63bit?) by the maximum planned number of shards and then set on each shard it's min/max value so ranges will not overlap?

chiph• 6 days ago

Because if the business grows, then you will need to add servers, and reallocate each existing shard's min/max values. If you left room to grow (divide amongst 2^31 instead of 2^63) you can go a long way before you have to solve that problem. If the business turns out to be wildly successful, you'd probably set up a whole new pool anyway and migrate over (and get a new set of pre-allocated ID ranges).

This might be the perfect case to use an UUIDv7 as a key instead of a number.

javier2• 6 days ago

low-traffic auto increment like user creation can be relatively performant by reserving batches up front, then using those in each shard.

But the use-case for this is mostly if you do not need, or have very limited use for anything cross-shard.

bddicken7• 6 days ago

A lot of what you're referring to is dictated by the sharding strategy. Vitess and Neki both let you configure this via the VSchema / data topology (That's what I'm getting at here)

https://planetscale.com/blog/making-768-servers-look-like-1#...

This decision matters a ton. I drilled into this specific point on sharding in one of my articles from awhile back:

https://planetscale.com/blog/database-sharding

This is something you face any time you shard data, no matter the system. Single-shard queries are preferred to cross-shard ones. We want 99% of what we do to be single shard, but occasionally cross-shard work is unavoidable.

drdexebtjl3• 6 days ago

We want 99% of what we do to be single shard, but occasionally cross-shard work is unavoidable.

Why optimize for the 1% and put the logic in a database proxy, then? It’s a leaky abstraction.

Require the application to explicitly and loudly make a query for each shard and collate the results.

zinodaur• 7 days ago

Sibling post has author answering questions in comments: https://news.ycombinator.com/item?id=48925420

groundzeros201511• 7 days ago

I disagree with the opening premise:

A single database server cannot handle such demand, so we must spread the queries and data out across many servers with database sharding

Did you max out the capacity of the best server you can buy?

Such a database can serve millions of customers (the numbers given).

You always want to scale up the other parts first, request handlers, caching, etc. The day you can no longer inspect the essential state of your system is the day your company better be included in NASDAQ and ready to pay a few hundred engineers 300k salaries.

anonzzzies2• 7 days ago

Well, they are selling this thing so they don't want you to buy a big server (with a read replica) as that's much cheaper.

farslan• 6 days ago

That's not true! We have demand for bigger machines and we also sell them. You can go checkout the PlanetScale website. See: https://x.com/samlambert/status/2077197049129587150

There are truly customers that bigger machine no longer cuts.

Disclaimer: I'm an Engineer at PS.

bddicken7• 6 days ago

We have tons of customers who do exactly this. It's great. Sharding is for customers who out grow this path.

p1necone• 7 days ago

Most non FAANG orgs could probably serve all their customers from postgres on a laptop.

don-code• 6 days ago

Let's hypothesize this is true.

I worked at a startup that had _money_ - a lot of it - flowing in. Stakeholders wanted to see growth, which meant features. They did not want to see us making platform improvements; those didn't show well to clients. Best throw money at the problem, rather than sacrifice the all-important features.

We had a number of architectural quirks that reflected this. One was that we ran our databases in AWS on ephemeral instance store. Yes, the kind that doesn't persist when you stop or lose the instance. The kind that you should never run a database on. We did it so that we could join them eight of them together in RAID 0 on the biggest instance types, and pull 400,000 IOPS to the disk that way. We paired this with hot spares of each shard, as well as hourly backups.

We did this to support a Rails / ActiveRecord data model, for data that should never have been part of a Rails data model. We had exactly one person working part-time on query optimization.

The maintenance burden was immense. The AWS bill, even more so. But again, we are hypothesizing that we could host all of this data on a laptop.

To an extent, maybe up until our thousandth customer or so, I actually think we could have. But we wouldn't have spent most of our time working on _features_ - we'd have instead spent most of our time trying to performance optimize. That would've meant the investors wouldn't have seen growth, which in turn would've highly impacted our success. We had a well defined domain, and optimizing the queries for performance was not it.

jackb40403• 7 days ago

I found the article very helpful from a technical perspective, and didn't focus on the number too much, as it could easily be swapped and the decision-making process for when to shard is kinda out of scope.

But I hadn't considered this, so thanks for pushing back. Good to keep in mind their incentives.

I will say, since their product is a proxy whose interface is a single SQL connection, you should in theory be able to do dev queries through that black box, much the same as application queries? What is so scary here that it would require a hundred engineers?

groundzeros201511• 7 days ago

you should in theory be able to do dev queries through that black box

Because it’s a leaky abstraction which is trying to make guarantees over network connections which are extremely difficult to make within the same kernel.

A few questions I would start with:

- is the system even ACID compliant?

In my reading of this article, no.

- is my sql feature set limited? Will it enforce all constraints? Or are their cross-shard limitations?

For example the article doesn’t discuss transactions or how they would roll back, or how they guarantee a consistent view of data.

- how does it respond to error?

- how does it respond to load?

This is a complex system and complexity breeds bugs. But now you don’t have the tools or procedures to investigate those bugs because you can’t poke the system at desk with tools. You can’t run experiments; you can’t even see all the data.

anichhangani• 7 days ago

Surely the cost of running sql server on premium hardware with replication would be more than running on commodity hardware with sharding?

groundzeros201511• 7 days ago

Only if your engineering resources and free and unbounded.

Even then I would probably use those resources to optimize software instead.

In the physical world of trucks and cranes no company would make that mistake to try to save 30-80k.

hilariously2• 6 days ago

It depends on who you are paying for it, but generally a distributed system is harder to reason about, harder to fix, has weirder edge cases, and much more easily get into situations where it requires even MORE expertise to fix than just having a big honking server.

When you start calculating things that are not just the server, the single server looks cheaper and cheaper. How do you get a consistent backup? How do you do DR? How do you tune queries when it could go to this node or that node? Now writes are going to be significantly slower if you need multi-node commit because no matter what you are racing the speed of light on the network.

skeptic_ai2• 6 days ago

Hetzner has this for 100usd a month, 256gb ram can handle quite a lot of traffic already

€84.70 max. per month €0.1357 per hour CPU Intel Xeon E5-1650V3 RAM 256 GB Drives 2 × 6.0 TB Enterprise HDD Location #FSN1-DC1 Information IPv4 ECC iNIC

Tostino• 6 days ago

Lol that isn't a database server. Come on, if it has hard drives rather than (good) SSD in 2026, it's not a server you should be using for databases unless it's for something with next to no load, and you are also running your application server on the same machine.

exiguus2• 6 days ago

As I understand the author: They describe the journey of scale from a single database server over read replicas to sharding. And its not only about a single server, its also about network (backup, restore).

bddicken7• 6 days ago

Spreading requests out across hundreds, thousands, and in some cases even more is precisely what is done in the industry for big databases! Good examples:

cashapp: https://code.cash.app/planetscale-metal github: https://github.blog/engineering/infrastructure/partitioning-... etsy: https://www.etsy.com/codeascraft/migrating-etsyas-database-s...

These companies could not realistically operate off a single database server.

groundzeros201511• 6 days ago

These companies could not realistically operate off a single database server.

I want to see it fail first. I suggest their org chart has more to do with their architecture than database performance.

Even so you’re in the category I said. Hundreds of expensive engineers maintain this stuff.

srcreigh• 6 days ago

The cashapp post is actually working towards GPs point. It explains that networked storage MySQL was unreliable and expensive. They migrated to $fancytool which offers a db instance with attached local nvme.

While cashapp may actually need sharding, there are so many companies who are overpaying for shitty performing network storage databases.

Not to mention you are subject to cloud provider networking and compute allocation code. They change it. Big slow network storage DB suddenly gets even worse and you don’t have leverage to have it fixed on their end.

amazingamazing• 6 days ago

and if your one beefy server goes down? oh, now you want a replica. so much for one beefy machine.

dizhn• 4 days ago

In the last 10 year or so my 2 beefy machines had much better uptime than the top clouds. :)

I am not suggesting you do this but some businesses can actually be down a little bit, like my non-IT one. I've had issues in the past with email. If the issue happens after business hours and resolves before start of business next day, nobody will even notice.

Hugsbox• 7 days ago

Took me an embarrassing amount of time to realize this is an ad.

foxhill• 7 days ago

i do wonder how something like this can be generally implemented. i presume this must only support a subset of SQL/plpgsql, as some things would be.. utterly insane to manage manually. e.g., if i have a table with a btree-gist overlap constraint, or some inclusion-exclusion check-constraint (or literally any constraint that requires multiple rows to be fully determined - there are quite a lot of them), how on earth does this work?

there's a reason why postgres writing is (mostly) serialised (asterisk) to a single writer (asterisk asterisk). something something ACID, but in short by having multiple writers improves availability, but weakens integrity.

skeptic_ai2• 6 days ago

How does Sharding works when You do complex joins ? Seems tricky , runs on each server and gets data back and aggregate it again?

kjellsbells• 6 days ago

I sometimes feel that when the industry moved from pets to cattle, what really happened is that the cattle turned out to need an exotic farm to live on, negating the savings. You can have a few honking servers or you can hand massage exotic k8s setups on your fleet. Pick your poison, but dont delude yourself that the TCO of the latter is lower than the former.

metalliqaz• 6 days ago

what did they use to make those diagrams/animations?

bddicken7• 6 days ago

Hey, author here.

Technically, they're powered by js + gsap + svg.

Process wise (for most of them) I sketched them out in advance in excalidraw for figure out layout, then passed these along to cursor to have it build out an initial draft from the image, then used some styling rules to get all the styles inline, then did a bunch of fine-tuning.

themgt• 6 days ago

Even with a large database servers (10s of CPU cores, 100s of gigabytes of RAM) bottlenecks arise pretty quickly.

Err, do they? For what percent of real world use cases?

The database can scale to handle more traffic by adding replicas. An extreme example of this is OpenAI's use of 50 replicas on a single Primary.

So an extreme example is OpenAI needing 50 replicas, but we're doing five blades ... err, we're doing 768 servers because the need arose "pretty quickly"?

When we needed to store a petabyte of data (one million gigabytes), we'd need many more shards

For who? The United States government? How many end-users are running 1PB Postgres database on DBaaS?

exiguus2• 6 days ago

Personally, I know several databases where single tables have +500GB and the database has +100TB. With this huge databases the restore and backup process over network become indeed a bottleneck. So I can agree with the author. Also, the author does not say that they can't start with a single database server and just read replicas and max hardware out. Real world use cases with +100TB I know about are Stock Market, Traffic Data, Warehouses, Analytics and Monitoring.

bddicken7• 6 days ago

So an extreme example is OpenAI needing 50 replicas, but we're doing five blades ... err, we're doing 768 servers because the need arose "pretty quickly"?

If you read the OpenAI article, you'll see that they actually used sharding to offload a bunch of work from their "1 primary 50 replicas setup"

>> "To mitigate these limitations and reduce write pressure, we’ve migrated, and continue to migrate, shardable (i.e. workloads that can be horizontally partitioned), write-heavy workloads to sharded systems such as Azure Cosmos DB..."

The 768 servers and 1PB example is just one of many configurations. A business with 10TB may choose to go from a monolithic database to a 8-shard setup to improve backup times, eliminate single-point-of-failure, have more breathing room for scaling.

hasyimibhar• 6 days ago

I'm surprised no one has mentioned Multigres yet, they are the competitor of Neki. I'm a big fan of both and has been following them since they were announced last year. I think this blog post is the first time they are talking about the internals of Neki. In contrast, Multigres is being built in public since day 1, you can see their high-level architecture here [1], though I'm still waiting for more details on their sharding model.

[1] https://multigres.com/docs/architecture

nazgulsenpai• 6 days ago

Most applications you've ever used function in this way, or at least did early in their existence.

I'm old enough that this is not true.

mike_hearn4• 6 days ago

I should start by disclosing that I work part time in the Oracle Database group, but - of course - my HN account is entirely my own, despite occasional mild shilling. The article itself is shilling for PlanetScale so that seems OK.

The author - certainly not deliberately! - says some untrue things about relational databases. The most important one is this:

To understand why sharding is a necessary part of scaling relational databases...

But sharding isn't a necessary part of scaling relational databases. It's really just a requirement of simple databases like Postgres and MySQL.

If you want a relational database cluster that really does make 768 servers look like one, then you want what Oracle calls RAC ("real application clusters"). Your cloud will probably rent you access to one under a name like Autonomous Database. Self hosted it may be called ExaData, which is a unified hardware/software "rent a rack" style offering. You may be surprised to discover that it's not much more expensive than many managed Postgres offerings.

RAC can scale a non-sharded relational database horizontally. That means all queries can access all data, all SQL features like sequences and joins work, any server can take part in transactions with any other and in general it looks exactly like a really big single machine would. In other words, it's a synchronous multi-write-master system.

RAC scales very well. 768 servers is well within reach as long as your query patterns scale too i.e. don't all contend on writing to one row. Behind the scenes it uses a dedicated high speed RDMA network with lock coordination to transfer data blocks directly between nodes, never hitting disk for memory that's already in the buffer cache.

Additionally RAC is fully HA and supports rolling upgrades of the cluster whilst live. You don't need any NLBs or routers either. The client drivers automatically discover and load balance between nodes without needing intermediaries, transactions can start on one node and fail over to another without applications noticing, and so on. There's plenty of opportunity for caching and replication. You can run asynchronously replicated failover clusters, run multiple clusters in a Raft-driven globally coordinated super-cluster and can deploy coherent read-through caches anywhere; the main clusters will inform them the moment data in them becomes stale.

In other words, it can do a lot.

If for some reason you do need sharding then that's also supported with features like automatic sharding key distribution to client drivers that transparently route queries correctly, but most apps don't need this.

In case you're wondering why I say all this, firstly, obviously, I have a financial conflict of interest. But the database hasn't driven Oracle's stock price for a long time, so it's not a big one. These days it's all about cloud and AI.

No, the main reason is that HN fills up every month with blog posts where engineers talk about the incredible pain involved with scaling and running Postgres. And almost always, it's clear that they don't realize there's any alternative to that pain. It's not that they considered the options and then explain why they picked this one, it's that they think - as claimed in this article - that it's almost some fundamental limitation of reality itself, imposed by the laws of computer science.

There are lots of startups that lose time and money due to database problems they simply don't need to have. And that sucks. If they'd prefer to spend that time, pain and money to avoid using a DB from Oracle, fine, so be it. I won't argue with random devs about lawnmower memes. But if it's because they don't realize what's possible.... well, maybe someone will be helped by being aware of this. Database scaling problems are a choice, not an inevitability.

marcosdumay3• 6 days ago

Lol about buying Oracle for performance!

But anyway, do you have benchmarks from anybody not related to Oracle showing that performance? Because Oracle forbids talking about it...

mike_hearn4• 6 days ago

Not forbidden. You can email a specific address to share results/setup and get permission to publish if you want. Other commercial databases also do that, because there's so many ways to misconfigure a database to make it slow and competitors are strongly incentivized to do so.

The question is what you'd want to benchmark. For example, imagine testing Postgres with a write load that goes well beyond what a single machine can do. It would collapse and query latencies would go through the roof. A horizontally scaled DB would keep going and process all those queries. Would you accept this as evidence that Postgres is slow or would you say it's not valid to benchmark at traffic loads Postgres physically cannot handle, given it never claimed to scale horizontally? Stuff like this is where benchmarking gets complicated.

I used to work at a different company that sold a kind of database system. It was much faster than our nearest competitor, so we were surprised when that competitor claimed to an important customer they were just as fast as us. Their benchmark counted transactions that failed and rolled back due to overload (optimistic concurrency) as "successful".

g8oz• 6 days ago

Does something similar to RAC exist for other commercial databases like Microsoft SQL Server or IBM DB2?

mike_hearn4• 6 days ago

DB2 yes, SQL Server no.

There are some cloud databases that scale horizontally but they often only support a subset of SQL, or require careful design to avoid creating hot tablets due to using a shared nothing design e.g. due to hot read nodes.

perceptronas• 6 days ago

How do you deal with master failures for specific shard? Does switch happen automatically once server becomes unresponsive?

Making 768 servers look like 1

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