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Channel

SQL Ready | Базы Данных

@sql_ready

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

17,074subscribers

+1,712 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1002029862606
TypeChannel
Username@sql_ready
CreatedBetween 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live25 September 2026
Measurements held32
Confirmed unchanged1 time, most recently 25 September 2026
On Telegramt.me/sql_ready

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 97% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Growth

15,35117,07416,212.57 August 2026 — 15,362 subscribers8 August 2026 — 15,361 subscribers9 August 2026 — 15,360 subscribers10 August 2026 — 15,351 subscribers11 August 2026 — 15,743 subscribers12 August 2026 — 15,945 subscribers13 August 2026 — 15,981 subscribers14 August 2026 — 16,024 subscribers16 August 2026 — 16,040 subscribers17 August 2026 — 16,126 subscribers18 August 2026 — 16,224 subscribers19 August 2026 — 16,284 subscribers20 August 2026 — 16,353 subscribers21 August 2026 — 16,401 subscribers22 August 2026 — 16,422 subscribers24 August 2026 — 16,452 subscribers25 August 2026 — 16,502 subscribers26 August 2026 — 16,535 subscribers27 August 2026 — 16,542 subscribers28 August 2026 — 16,528 subscribers29 August 2026 — 16,543 subscribers30 August 2026 — 16,556 subscribers31 August 2026 — 16,612 subscribers2 September 2026 — 16,616 subscribers3 September 2026 — 16,627 subscribers5 September 2026 — 16,622 subscribers8 September 2026 — 16,778 subscribers11 September 2026 — 16,933 subscribers13 September 2026 — 16,953 subscribers14 September 2026 — 16,960 subscribers16 September 2026 — 16,976 subscribers25 September 2026 — 17,074 subscribers7 August 202625 September 2026
32 measurements spanning 49 days, net +1,712. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 15,093–17,332 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)SubscribersChange
25 Sept 2026, 20:2017,074+98
16 Sept 2026, 20:5816,976+16
14 Sept 2026, 20:5916,960+7
13 Sept 2026, 07:5616,953+20
11 Sept 2026, 08:4116,933+155
8 Sept 2026, 14:3816,778+156
5 Sept 2026, 05:5916,622-5
3 Sept 2026, 13:4116,627+11
2 Sept 2026, 09:5416,616+4
31 Aug 2026, 12:1316,612+56
30 Aug 2026, 12:0716,556+13
29 Aug 2026, 11:5716,543+15
28 Aug 2026, 12:3516,528-14
27 Aug 2026, 12:0316,542+7
26 Aug 2026, 14:5316,535+33
25 Aug 2026, 13:0216,502+50
24 Aug 2026, 10:4516,452+30
22 Aug 2026, 20:4416,422+21
21 Aug 2026, 09:1416,401+48
20 Aug 2026, 10:2416,353first reading

Engagement

48 posts held, back to 24 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 59 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
7.40%
avg views ÷ 17,074 subscribers
Avg views / post
1,260
9 posts measured
Reaction rate
1.88%
reactions ÷ views · ER floor
Posts in window
9
of 48 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 3 September 2026
Posts held48 (24 July 2026 – 3 September 2026)
Views total11,374
Reactions total214
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 09:46 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Video runtime
1m 55s
Average length
10s

Measured directly from 12 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.

Reaction mix

1,225 reactions across 47 posts, in 6 distinct kinds. The most used accounts for 32.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥39332.1%
❤37930.9%
👍32226.3%
🤝1169.47%
👎120.98%
😁30.245%

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 47 of the 48 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 1,225 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 48 most recent posts we hold, published 24 July 2026 to 3 September 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.

Recent posts

3 Sept 2026, 06:12 UTC614 views18 reactionsread 3 September 2026
Photo

🐱 Нашел крайне занимательную статью на Хабре: «Условная агрегация в SQL: ускоряем отчеты, избавляясь от лишних JOIN-ов и подзапросов»! В этой статье: • Узнаете, как ускорять сложные SQL-запросы с помощью условной агрегации; • Разберёте применение CASE и FILTER вместо множества подзапросов и JOIN-ов; • Посмотрите на примерах, как сделать SQL-код быстрее, чище и проще для поддержки. 🔊 Продолжай читать на Habr! ➡️ SQ…

❤6👍6🔥4🤝2

2 Sept 2026, 06:12 UTC≈1,120 views23 reactionsread 3 September 2026
Video

✍️ Архитектура высоконагруженных систем — подробный материал по проектированию Highload! Здесь разобраны ключевые вещи, с которыми сталкиваются при разработке нагруженных систем: RPS, latency и throughput, вертикальное и горизонтальное масштабирование, индексы, репликация и шардирование баз данных, кеширование, брокеры сообщений и др. Есть практические примеры с MySQL, PostgreSQL, Kafka и Tarantool, а также инструме…

👍10❤5🔥5🤝3

1 Sept 2026, 13:12 UTC≈1,070 views26 reactionsread 3 September 2026

Почему коррелированные подзапросы могут снижать производительность SQL-запроса! Коррелированные подзапросы удобны: внутри них можно обращаться к значениям текущей строки внешнего запроса. Проблема в том, что оптимизатор может выбрать план, при котором такой подзапрос будет выполняться повторно для каждой строки внешней выборки. На больших объёмах данных это может стать узким местом. Например: SELECT u.id, u…

❤13👍6🔥4🤝3

1 Sept 2026, 11:12 UTC≈1,180 views10 reactionsread 3 September 2026
Photo

Уже очевидно, что ВАЙБКОДИНГ — главный навык ближайших лет Посмотрите сами. ИИ уже забирает на себя работу целых команд: пишет код, закрывает задачи джунов и позволяет стартапам запускать продукты в 2–3 раза меньшим составом. То, на что раньше нужны были несколько разработчиков, сегодня всё чаще делает один человек с ИИ-агентами. И это только начало. Те, кто освоит вайбкодинг сейчас, смогут быстрее запускать проект…

👎8❤2

1 Sept 2026, 06:12 UTC≈1,270 views24 reactionsread 3 September 2026
Photo

📂 Шпаргалка по Backend-разработке! Например, REST используется для построения API, Redis помогает кэшировать данные, а Docker позволяет упаковать приложение вместе со всеми его зависимостями. На картинке — основные направления Backend-разработки: языки программирования, базы данных, API, авторизация, серверы, контейнеризация, CI/CD и мониторинг. Полезная карта того, что стоит изучить Backend-разработчику. Сохрани,…

❤12🔥7👍5

31 Aug 2026, 17:37 UTC≈1,290 views32 reactionsread 3 September 2026
Photo

Научите оптимизатор понимать ваши данные! PostgreSQL по умолчанию считает, что значения в разных колонках независимы друг от друга. Но в реальных данных это часто не так. Например, если city = 'Paris', то country почти всегда будет 'France'. Без этой информации оптимизатор может сильно ошибиться при оценке количества строк и выбрать неудачный план. EXPLAIN SELECT * FROM users WHERE country = 'France' AND city = '…

🔥16❤9👍7

31 Aug 2026, 06:12 UTC≈1,410 views27 reactionsread 3 September 2026
Video

🤔 SQL Lab — интерактивная платформа для изучения и практики SQL! Сайт для тех, кто хочет освоить SQL через работу с запросами. Код пишется прямо в браузере: выполняете запрос, сразу видите результат и получаете автоматическую проверку решения. Обучение построено от базовых SELECT и ORDER BY до JOIN, подзапросов, транзакций, индексов, оптимизации запросов и PostgreSQL. Есть структурированные курсы с теорией и практик…

❤12👍10🔥5

29 Aug 2026, 12:10 UTC≈1,770 views30 reactionsread 3 September 2026
Photo

UNIQUE и NULL в PostgreSQL 15! До PostgreSQL 15 уникальные ограничения считали NULL разными значениями. Это означало, что таблица спокойно принимала сколько угодно строк с NULL, даже если на колонке стоял UNIQUE. CREATE TABLE users ( email text UNIQUE ); INSERT INTO users VALUES (NULL); INSERT INTO users VALUES (NULL); Обе вставки выполнятся успешно. Если NULL тоже должен быть уникальным, приходилось придумыв…

🤝12❤9👍9

29 Aug 2026, 08:12 UTC≈1,650 views24 reactionsread 3 September 2026
Photo

Photo, posted without a caption

🔥13🤝7👍4

28 Aug 2026, 06:12 UTC≈1,970 views22 reactionsread 3 September 2026
Photo

❤️ Интересная статья на Хабре: «Что такое RAGFlow и с чем его едят»! В этой статье: • Разберётесь, как RAGFlow помогает LLM работать с внутренними документами и снижать количество галлюцинаций; • Узнаете, чем RAGFlow отличается от классического RAG и как он обрабатывает PDF, таблицы, схемы и сканы; • Посмотрите, как развернуть RAGFlow и использовать его для баз знаний, техподдержки и аналитики. 🔊 Продолжай читать н…

🔥11👍6🤝5

27 Aug 2026, 06:12 UTC≈2,000 views35 reactionsread 3 September 2026
Photo

📂 Шпаргалка по нормализации баз данных в MySQL! Например, 1NF требует атомарных значений, 2NF избавляет от частичных зависимостей, а 3NF — от транзитивных. Для более сложных схем пригодятся BCNF и 4NF. На картинке — основные нормальные формы с требованиями, примерами и пользой каждой из них. Сохрани, чтобы не потерять! ➡️ SQL Ready | #ресурс

🔥16❤10🤝8👎1

26 Aug 2026, 06:12 UTC≈2,050 views31 reactionsread 3 September 2026
Photo

🖥 PostgreSQL — блокировки строк и конкурентный доступ! Шпаргалка по механизмам синхронизации параллельных транзакций в PostgreSQL: защита строк от конкурентных изменений и удаления, управление ожиданием и пропуском занятых строк, явная блокировка таблиц и диагностика ожидающих блокировок. Помогает контролировать конкурентный доступ и корректно реализовывать транзакционные сценарии. ➡️ SQL Ready | #шпора

❤13👍10🔥8

Showing the 12 most recent of 48 posts we hold for @sql_ready. 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.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

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.

Cite this entry

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 25 September 2026 — this entry's latest reading, not the date you are reading this.

“SQL Ready | Базы Данных” (@sql_ready), 17,074 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/sql_ready.

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.