Command-line Tools can be 235x Faster than a Hadoop Cluster (2014)

In that example the idea is that feudalism represents a form of "community property", which though owned by a feudal lord in the final instance is in practice shared. Capitalism then "negates" that by making the property purely private, before communism negates that again and reverts to shared property but with different specific characteristics.

The three key principles of Hegels dialectics comes from Heraclitus (the idea of inherent conflict within a system pulling it apart), Aristotle (the paradox of the heap; the idea that quantitative changes eventually lead to qualitative change), and Hegel himself (the "negation of the negation" that was popularised by Marx in Capital; the idea that a driven by inherent conflict, qualitative changes will first change a system substantially, before reversing much of the nature of the initial change, but with specific qualitative differences).

The idea is known to have been simultaneously arrived at by others in 19th century too, at least (e.g. at least one correspondent of Marx' came up with it independently), and it's quite possible variations of it significantly predates both Marx and Hegel as well.

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But I've sent it to you in email - check it out if you're interested.

At a theoretical level, as a sysadmin, I learned the theoretical capabities by reading datasheets for CPUs, motherboards (historically, also chipsets, bridge boards, and the like, but those are much less irrelevant), and storage products (HBAs/RAID cards, SAS expander chips, HDDs, SSDs). Make sure you're always aware of the actual payload bandwidth (net of overhead), actual units (base 2 or base 10) and duplex considerations (e.g. SATA).

From a more practical level, I look at various vendors' actual products, since it doesn't matter (for example) if a CPU series can support 8 sockets if the only mobos out there are 2- and 4-socket.

I also look at whatever benchmarks were out there to determine if claimed performance numbers are credible. This is where sometimes even enthusiast-targeted benchmark sites can be helpful, since there's often a close-enough (if not identical) desktop version of a server CPU out there to extrapolate from. Even SAS/SATA RAID cards get some attention, not in a configuration worthy of even "medium" data, but enough for validating marketing specs.

That's probably better, since it'll scale a bit better with technological improvements. The problem is, it doesn't have quite the clever sound to it, especially with the numbers and dollars.

Now, the other main problem is that, though the cost of a workstation is fairly well-bounded, the cost of that medium-data server can actually vary quite widely, depending on what you need to do with that data (or, I suppose, how long you might want to retain data you don't happen to be doing anything to right at that moment).

I suppose that's part of my point, that there's a mis-perception that, because a single server (including its attached storage) can be so expensive, to the tune of many tens of thousands of (US) dollars, that somehow makes it "big" and undesireable, despite its potentially close-to-linear price-to-performance curve compared to those small 1U/2U servers. Never mind doing any reasoned analysis of whether going farther up the single-server capacity/performance axis, where the price curve gets steeper is worth it compared to the cost and complexity of a distributed solution.

> are there any resources you'd recommend for learning about what's available in the land of that higher-end rackmount equipment?

Sadly, no great tutorials or blogs that I know of. However, I'd recommend taking a look at SuperMicro's complete-server products, primarily because, for most of them, you can find credible barebones pricing with a web search. I expect you already know how to account for other components (primarily of concern for the mobos that take only exotic CPUs).

As I alluded in another comment, you might also look into SAS expanders (conveniently also well integrated into some, but far from all, SuperMicro chassis backplanes) and RAID/HBA cards for the direct-attached (but still external) storage.

That's primarily because I'm aware of the variability that random access injects into spinning disk performance and that 10GE is now common enough that it takes more than just a single (sequentially accessed) spinning disk to saturate a server's NIC.

Plus, if you're talking about a (single) local spinning disk, I'd argue that's a trivial/degenerate case, especially if compared to a more expensive SSD. Does my assertion stand up better if I it had "of comparable cost" tacked on? Otherwise, the choice doesn't make much sense, since a local SSD is the obvious choice.

My overall point is that, though one particular workload may make a certain technology/configuration appear superior to another [1], in the general case, or, perhaps most importantly, in the high performance case, to have an eye on the bottlenecks, especially the ones that carry a high incremental cost of increasing their capacity.

It may be that people think the network, even 10GE now, is too cheap to be one of those bottlenecks, arguably a form of fallacy [2] number 7, but that ignores the question of aggregate (e.g. inter-switch) traffic. 40G and 100G ports can get pricey, and, at 4x and 10x of a single server port, they're far from solving fallacy number 3 at the network layer.

The other tendency I see is for people not to realize just how expensive a "server" is, by which I mean the minimum cost, before any CPUs or memory or storage. It's about $1k. The fancy, modern, distributed system designed on 40 "inexpensive" servers is already spending $40k just on chasses, motherboards, and PSUs. If the system didn't really need all 80 CPU sockets and all those DIMM sockets, it was money down the drain. What's worse, since the servers had to be "cheap", they were cargo-cult sized at 2U with low-end backplanes, severely limiting existing I/O performance. Then, to expand I/O performance, more of the same servers [3] are added, not because CPU or memory is needed, but because disk slots are needed and another $4k is spent to add capacity for 2-4 disks.

[1] This has been done on purpose for "competitive" benchmarks since forever

[2] https://en.wikipedia.org/wiki/Fallacies_of_distributed_compu...

[3] Consistency in hardware is generally something I like, for supportability, except it's essentially impossible anyway, given the speed of computer product changes/refreshes, which means I think it's also foolish not to re-evaluate when it's capacity-adding time after 6-9 month.

You can have minimally relational data such as URL : website, but that's still improved by going URL : ID, ID : website because you can insert those ID's into the website data.

Now plenty of DB's have terrible designs, but there I have yet to year of actually non relational data.

Although that is true in principle, in reality that results in the messes I see around me where a small startup (but this often goes for larger corps too) has a plethora of tech running it fundamentally does not need. If your team’s expertise is Laravel with MySql then even if some project might be a slightly better fit for node/mongo (does that happen?), I would still go for what you know vs better fit as it will likely bite you later on. Unfortunately people go for more modern and (maybe) slightly better fit and it does bite them later on.

For most crud stuff you can just take an ORM and it will handle everything as easily as nosql anyway. If your delivery and deployment process have a rdbms, it will be natural anyway and likely easier than anything nosql unless it is something that is only a library and not a server.

Also, when in doubt, you should take a rdbms imho, not, like a lot of people do, a nosql. A modern rdbms is far more likely to fit whatever you will be doing, even if it appears to fit nosql better at first. All modern dbs have document, json/doc storage built in or added on (plugin or orm) : you probably do not have the workload that requires something scaleout like nosql promises. If you do, then maybe it is a good fit, however if you are conflicted it probably is not anyway.

No, there are not. In 99% of applications, the data is able to be modeled relationally and a standard RDBMS is the best option. Non-relational data is the rare exception, not the rule.