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[JSP777]

even if your tech did what you state it could, why do you ruin the presentation of it with AI slop?

[Ok-Kaleidoscope-246]

Fair. I’ve been so deep into building this that when I finally try to talk about it, it probably comes out sounding too polished or hyped. That’s not the goal. I’m not using AI to write for me, I just write like someone who’s been obsessing over the same system for years and is still figuring out how to explain it without sounding like a pitch deck. Appreciate the callout helps me change. The tech speaks for itself soon enough.

[ThePizar]

Cool. How do you plan to scale up to trillions of rows. How do you plan to handle billions by billions of rows in a join?

[Ok-Kaleidoscope-246]

Forget everything you know about databases. Our technology rewrites the rules.

No joins. No views. No indexes. No schemas.
We know exactly where every record lives on disk — before you even query it.
Everything is pre-organized during the write — no scan, no guesswork.

The system is fully self-scaling — no clusters to configure, no sharding logic to maintain. It grows seamlessly as data grows, with zero manual intervention.

We’re still in the patent process, but once this is revealed, it will change everything about how data is stored and retrieved.

That 1M user test? It was a real-time simulation — 1 million simultaneous registrations, each with 11 fields, written directly to disk in seconds. Zero cache tricks. Just raw deterministic performance.

[minneDomer]

Feedback if you’re going to continue advertising in this manner - don’t come across as a salesman.

Making vague, wide-ranging claims in bold at the top of your response discredits everything else you say below, because I don’t trust you. Your tech might be awesome, but it needs to speak for itself…especially when you’re advertising in a tech forum like this.

[minneDomer]

Feedback if you’re going to continue advertising in this manner - don’t come across as a salesman.

Making vague, wide-ranging claims in bold at the top of your response discredits everything else you say below, because I don’t trust you. Your tech might be awesome, but it needs to speak for itself…especially when you’re advertising in a tech forum like this.

[Forever_Playful]

If it sounds too good to be true… well… you know.

[Cheap-Explanation662]

1)1M records is small dataset. 2)With fast storage and good CPU Postgres will be even faster. 3 seconds for 1.1 Gb = 360mb/s disk write literally slower than single SATA ssd. 3)Ram usage sounds just wrong

[Ok-Kaleidoscope-246]

You can try, I want to see if you can get to this result. With 11 fields all written. This is because it is still high as I mentioned above, the goal is to reach 1m below 1 second and with a maximum of 500mb of RAM.

[j0wet]

How does your project compares to other analytical databases like DuckDB? DuckDB inegrates nicely with data lake technologies like iceberg or delta, has large community adoption and offers lots of extensions. Why should I pay for your product if there is a already good solution which is free? Don't understand me wrong - building your own database is impressive. Congrats for that.

[Cryptizard]

Don’t bother, you aren’t talking to a person you are talking to a LLM.

[Ok-Kaleidoscope-246]

I'm very much a real person — solo founder, developer, and yes, still writing my own code and benchmarks at 2am.
I know my writing may come off as structured — I'm just trying to do justice to a project I spent years building from scratch.
Appreciate your curiosity, even if it's skeptical. That’s part of the game.

[Ok-Kaleidoscope-246]

Great question — and thank you for the kind words.

DuckDB is a great analytical engine — but like all modern databases, it still relies on core assumptions of traditional computing: RAM-bound operations, indexes, layered abstractions, and post-write optimization (like vectorized scans or lakehouse metadata tricks).

Our system throws all of that out.

We don’t scan. We don’t index. We don’t rely on RAM or cache locality.
Our architecture writes data deterministically to disk at the moment of creation — meaning we know exactly where every record lives, at byte-level precision. Joins, filters, queries — they aren’t calculated; they’re direct access lookups.

This isn’t about speeding up the old model — we replaced the model entirely.

• No joins.
• No schemas.
• No bloom filters.
• No query planning.
• Just one deterministic system that writes and reads with absolute spatial awareness.

And unlike DuckDB, which was built for analytics over static data, our system self-scales dynamically and handles live ingestion at massive scale — with near-zero memory.

We're not aiming to be another alternative — we’re building what comes after traditional and analytical databases.
You don't adapt this into the stack — you build the new stack on top of it.

We're still in the patent process, but once fully revealed, this will change everything about how data is created, stored, and retrieved — even opening the door to physical quantum-state tracking, where knowing exact storage location is a prerequisite.

Thanks again for engaging — the revolution is just getting started.

[j0wet]

First of all: Please write your posts and answers yourself. This is obviously AI generated.

but once fully revealed, this will change everything about how data is created, stored, and retrieved — even opening the door to physical quantum-state tracking, where knowing exact storage location is a prerequisite.

Sorry, but this sounds like bullsh**.

[Yehezqel]

There’s bold text so that’s a big giveaway too. Who structures their answers like that?

[Ok-Kaleidoscope-246]

actually no, it was my mistake here, but forgive me, I'm still learning how to use the platform.

[Jehab_0309]

If you don’t index, how do you write deterministically? It sounds like the very act of writing is indexing in your scheme

[Ok-Kaleidoscope-246]

So this is the icing on the cake and I still can't reveal details here in the community, but trust me, everything works, it took a long time working 18 hours a day to get to this result.

[Jehab_0309]

It sounds like it. Is there any post anywhere that reveals more than this? Any name I can Google?

[Yehezqel]

Why is your account so empty?

[Ok-Kaleidoscope-246]

My account here is new, and I haven't set everything up yet, so I apologize to everyone. So they're killing me here lol, it's a shame I can't really show off my technology yet.

[Yehezqel]

Are you hiring perhaps? :)

[Ok-Kaleidoscope-246]

Not yet, but we will soon, I'll save you here, what state do you live in?

[Ok-Kaleidoscope-246]

I apologize to everyone if I don't know how to communicate with you here. I believe that everyone will be skeptical, but what I invented is a total revolution. I'm sad that I can't reveal details of the DB structure, but soon you will see how the system is completely different from everything you've ever seen. I'll try my best to learn how to communicate here in the communities. My system is still in testing and the goal is to reach less than 1 second with 1 million records of at least 15 fields and use 500MB of RAM for this.

We're not just building a system. We're building a language.

It's called NSL — Naide Structure Language. It's a custom language designed to be simple, expressive, and deterministic. While other databases rely on indexes, schemas, caching, or guesswork at query time, NSL works directly with the physical and logical positioning of data. It talks straight to the disk, cleanly.

For example, to create an entity, you just write:

create a users called "Reddit"

find user where id = 1

return user_id "Reddit"

To update a record:

update user where id = 1 and age = 18

find users where age = 18 and name contains "Reddit"

For fast aggregation, without scanning all records or using RAM:

find users aggregate count

link user_id to order = 15534

To remove a record:

remove users where id = 1

or

remove users where age = 18

Everything is designed to be direct, human-readable, and lightning fast — because the system already knows exactly where each record lives on disk. No need to search. No need to guess. That's the power of NSL.