Краткий справочник по типам данных к посту
🔥11custom 63032460846594807995💯4👾2🤔1
Signed Vladimir Lejn

Channel
@relational_databases
On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Polls · Citations · Handles named that no longer answer · Cite this entry
987subscribers
+0 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002413785982 |
|---|---|
| Type | Channel |
| Username | @relational_databases |
| Description | Канал айтишника о реляционных базах данных, SQL и модели данных. У нас тут много, очень много практических разборов)) Меня зовут Владимир Лунев (@lejnlune). Интересуюсь архитектурой систем и моделей данных. |
| Created | Between 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 8 August 2026 |
| Last confirmed live | 8 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/relational_databases |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Aug 2026, 00:35 | 987 | no change |
| 7 Aug 2026, 14:57 | 987 | first reading |
20 posts held, back to 29 July 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 28 June 2026. An engagement rate over an empty window would be a number about nothing.
Lifetime counters from Telegram’s own channel header, read 8 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
695 reactions across 20 posts, in 10 distinct kinds. The most used accounts for 54.2% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 377 | 54.2% | |
| custom 6303246084659480799 | 109 | 15.7% | |
| 👾 | 90 | 12.9% | |
| 💯 | 54 | 7.77% | |
| 🤣 | 33 | 4.75% | |
| 😱 | 15 | 2.16% | |
| 🌚 | 8 | 1.15% | |
| 🤔 | 4 | 0.576% | |
| 🤯 | 3 | 0.432% | |
| 🗿 | 2 | 0.288% |
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 20 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 695reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 29 July 2025 to 28 June 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @relational_databases. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 20 most recent posts we hold for this entry, published 29 July 2025 to 28 June 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Краткий справочник по типам данных к посту
🔥11custom 63032460846594807995💯4👾2🤔1
Signed Vladimir Lejn
👩💻 Типы данных в PostgreSQL: как они устроены и почему их выбор имеет значение Одна из самых распространенных ошибок при проектировании базы данных это выбирать типы данных по принципу "лишь бы поместилось". На самом деле тип данных определяет не только допустимые значения, но и способ их хранения, объем занимаемой памяти, производительность запросов и размер индексов. PostgreSQL предоставляет широкий набор встрое…
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Signed Vladimir Lejn
Всем привет)) Я вернулся, так что с этой недели будут новые посты, будем воскрешать канал. Пропадал из за загруженности на работе и своих проектах.
🔥52custom 630324608465948079912👾9
Signed Vladimir Lejn
🥳Всех с наступающим! Решил подвести, итоги года для канала. Создавая его в феврале, я даже не думал, что получу такой крутой отклик от вас. Нас уже +1к, чему я безумно рад. 🏆 Хочу поблагодарить каждого подписчика за то, что читаете мой контент, ставите реакции, пишите коменты. Вы лучшие! 🍑Немного статистики: за этот год, было написано 115 постов, получено 1.8к реакций и 78.8к просмотров 🔥Посты с самым большим ко…
🔥23👾8custom 63032460846594807994💯2
Signed Владимир Л.
0️⃣ NULL в SQL - не "ничего", а "неизвестно" Когда вы видите NULL в таблице, интуиция подсказывает: "Это просто пусто. Ничего нет. Поле не заполнено". Но реляционная модель намеренно отказывается от такого упрощения. Вместо "ничего" она вводит состояние неопределённости: значение существует, но нам о нём ничего не известно. Именно поэтому NULL - это не данные, а метаинформация о недостатке данных. И эта тонкость ло…
🔥27custom 63032460846594807999👾4💯3🌚1
Signed Владимир Лунев
💡 Реляционная модель, это не просто таблицы. Это договор между людьми Когда я только начал работать аналитиком, я думал, что база данных это просто место, где хранятся цифры. Потом я потратил два дня на отчёт, который оказался неверным, потому что не знал: поле status в таблице orders может быть NULL, если заказ ещё не обработан системой. Но документации по этому поводу не было и узнал я об этом потом только со сл…
🔥17custom 63032460846594807995💯4
Signed Владимир Лунев
🐘 От академического проекта до лидера open-source: история PostgreSQL Продолжим тему постов про историю SQL и СУБД, ранее мы уже разбирали: ➖ Как создатель MySQL потерял миллиарды ➖ Историю SQL: от лаборатории IBM до ядра современного ИТ Теперь настало время одной из самых популярных промышленных СУБД — PostgreSQL ❗️ Начало, проект "Ingres" Всё началось в 1986 году в Калифорнийском университете в Беркли. Группа …
🔥18custom 630324608465948079910👾4🤯2
Signed Владимир Л.
Если вы задумывались над тем, чем же все-таки занимаются аналитики, рекомендую подписаться на канал Data Brew! Канал ведет тот самый аналитик, который смог построить карьеру после курсов и сейчас продолжает расти профессионально. Автор 🤗 помогает в поиске работы 😊пишет о полезных для аналитиков хардах 🎁делится реальными историями с собеседований 🤬 рассказывает о боли аналитиков 😇 скидывает аналитические мемы Подпи…
🔥8👾5custom 63032460846594807995
Signed Владимир Л.
❗️ HAVING в SQL Многие думают, что оператор HAVING — это просто аналог WHERE, но после GROUP BY. Это упрощение, которое может привести к путанице. Давайте разберём настоящую теорию — шаг за шагом. Здесь нужно понимать, что SQL-запрос выполняется СУБД не в том порядке, в котором он написан человеком. Это критически важно для понимания HAVING. ❗️ Логический порядок с точки зрения исполнения СУБД (упрощённо): 1. FROM…
🔥33💯10👾6custom 63032460846594807992🤔1
Signed Владимир Лунев
Какой СУБД вы пользуетесь сейчас?
Shares as published, totalling 98%. No per-option vote count is published by Telegram, so none is shown.
🔥6custom 63032460846594807996🌚2💯1
Signed Владимир Лунев
Узнайте, почему ваши SQL-запросы тормозят 🤖 Медленные SQL-запросы могут стоить бизнесу миллионов: отчёты считаются часами, решения принимаются с задержкой, а ошибки в данных подрывают доверие к аналитике. На вебинаре Владимир Лунев, бизнес- и системный аналитик с 5-летним опытом работы в ритейле и IT, разберёт 7 реальных кейсов оптимизации SQL-запросов, которые помогали бизнесу принимать быстрые и точные решения. …
🔥10custom 63032460846594807996💯5🤔2🤣1
Signed Владимир Л.
📥 Гайд по LIMIT и OFFSET Когда вы работаете с большими таблицами, часто не нужны все строки сразу. Например, вы хотите: ➖ показать топ-10 самых дорогих товаров, ➖ вывести последние 20 заказов, ➖ сделать постраничную навигацию в приложении. ➖ вам просто лень писать фильтры, ведь для анализа/оценки хватит n-строк таблицы. НО учтите что будет полное сканирование таблицы! Для этого в SQL есть два оператора (точнее cla…
🔥19custom 63032460846594807998👾6
Signed Владимир Лунев
Showing the 12 most recent of 20 posts we hold for @relational_databases. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
Какой СУБД вы пользуетесь сейчас?
Shares as published, totalling 98%. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none.The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100.Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 20 most recent posts we hold, published 29 July 2025 to 28 June 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
@relational_databases named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
References a handle that is not a live channel — we have no record it ever was one.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 8 August 2026 — this entry's latest reading, not the date you are reading this.
“SQL: Реляционные базы данных” (@relational_databases), 987 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/relational_databases.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.