Telegram RegisterThe public register of Telegram
Telegram profile photo for Data Science. SQL hub

Channel

Data Science. SQL hub

@sqlhub

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Advertising · Posts · Posts recorded as deleted · Polls · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

36,025subscribers

+145 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001434942369
TypeChannel
Username@sqlhub
DescriptionПо всем вопросам- @workakkk @itchannels_telegram - 🔥лучшие ит-каналы @ai_machinelearning_big_data - Machine learning @pythonl - Python @pythonlbooks- python книги📚 @datascienceiot - ml книги📚 РКН: https://vk.cc/cIi9vo #VRHSZ
CreatedBetween 1 April 2019 and 31 October 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live10 November 2026
Measurements held61
Confirmed unchanged1 time, most recently 10 November 2026
On Telegramt.me/sqlhub

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 9 September 2026 and assigned it the closest of 31 fixed categories, at 92% 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 the other topics.

Growth

35,85436,16536,009.536,0256 August 202610 November 2026
61 measurements spanning 96 days, net +145. 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 35,807–36,212 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)SubscribersChange
10 Nov 2026, 11:0036,025-4
8 Nov 2026, 22:5436,029-10
7 Nov 2026, 15:1736,039-3
6 Nov 2026, 18:1836,042-10
4 Nov 2026, 15:3636,052-6
3 Nov 2026, 14:2736,058-11
2 Nov 2026, 13:0736,069-12
1 Nov 2026, 10:5036,081-10
31 Oct 2026, 12:1036,091-10
30 Oct 2026, 12:1736,101-13
29 Oct 2026, 12:1736,114-7
28 Oct 2026, 14:2636,121-18
27 Oct 2026, 11:1536,139-7
26 Oct 2026, 11:5636,146-12
25 Oct 2026, 09:0636,158-7
24 Oct 2026, 10:1636,165+5
23 Oct 2026, 10:0636,160+9
22 Oct 2026, 08:3036,151+109
20 Oct 2026, 22:3836,042-5
19 Oct 2026, 19:0736,047first reading

Engagement

112 posts held, back to 15 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 179 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
8.39%
avg views ÷ 36,025 subscribers
Avg views / post
3,020
23 posts measured
Reaction rate
0.337%
reactions ÷ views · ER floor
Posts in window
23
of 112 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. It is computed over the 22 of 23 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 November 2026
Posts held112 (15 July 2026 – 10 November 2026)
Views total69,540
Reactions total222
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Nov 2026, 05:44 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

Photos
≈1,210
Videos
≈100
Links
≈1,210

Lifetime counters from Telegram’s own channel header, read 11 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
5m 05s
Average length
44s

Measured directly from 7 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

1,378 reactions across 105 posts, in 12 distinct kinds. The most used accounts for 35.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍49435.8%
❤42230.6%
🔥28921.0%
😁553.99%
👎342.47%
🥰312.25%
😱151.09%
🤬120.871%
👏90.653%
🤔70.508%
🎉60.435%
🤯40.29%

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 110 of the 112 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 1,401 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 112 most recent posts we hold, published 15 July 2026 to 10 November 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.

Advertising

Ad load
8.93%
10 of 112 posts carry an ad marker
Regulatory tokens
10
posts carrying an erid · 9 distinct tokens
Median views · ads
2,320
over 10 measured posts
Median views · rest
2,960
over 102 measured posts

An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.

This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.

Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. They are printed side by side with the count behind each rather than as a ratio: an ad and an ordinary post are not otherwise matched — for topic, for length, for hour of day — so the gap between them is a description of two groups and not the effect of one being an ad.

Advertising tokens recorded on this entry
eridPostsFirst seenLast seen
2W5zFJogLHX221 August 202624 August 2026
2VSb5xkQt6E117 September 202617 September 2026
2VtzquuHE37119 August 202619 August 2026
2VtzqvJYWyT18 October 20268 October 2026
2VtzqwtpEpd19 October 20269 October 2026
2Vtzqx3mtnf120 August 202620 August 2026
2W5zFGPtHER116 July 202616 July 2026
2W5zFGnMUNe110 November 202610 November 2026
2W5zFJRGV8517 October 20267 October 2026

A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.

Measured over the 112 most recent posts we hold, published 15 July 2026 to 10 November 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.

Recent posts

Telegram’s own ‘edited’ marker: 1 of 23 posts held from the last 30 days (4.35%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

10 Nov 2026, 09:29 UTC≈1,160 views3 reactionsread 11 November 2026
Advertisementerid 2W5zFGnMUNePhoto

🦾 Что надо знать про работу LLM перед внедрением После открытого урока у вас сложится ясная картина того, как устроены языковые модели. Вы будете понимать, почему модель ведет себя именно так, и что важно учесть, прежде чем встраивать ее в свой проект. Урок пройдет 12.11 в 20:00 и подойдет тем, кто пользуется LLM, но не знает, как они устроены внутри, и хочет разобраться в основах до того, как внедрять их в проект.…

👎2👏1

9 Nov 2026, 11:04 UTC≈1,730 views14 reactionsread 11 November 2026
Photo

RAG без векторной базы: PageIndex набрал 40 тысяч звёзд на GitHub PageIndex предлагает другой подход к поиску информации в документах. Вместо embeddings, разбиения текста на чанки и векторного поиска используется иерархический индекс и рассуждения LLM. Система строит дерево разделов документа, а затем модель последовательно выбирает нужные ветки и находит ответ с указанием источника. Такой подход особенно полезен …

❤9🔥4🥰1

6 Nov 2026, 10:37 UTC≈2,370 views16 reactionsread 11 November 2026

SQL-задача с подвохом: найдите пользователей, которые вернулись после 30 дней молчания Представьте, что вы анализируете активность пользователей сервиса. Нужно найти тех, кто вернулся после длительного перерыва. Есть таблица PostgreSQL: CREATE TABLE events ( user_id INT, event_time TIMESTAMP ); INSERT INTO events VALUES (1, '2026-10-01 10:00'), (1, '2026-10-01 12:00'), (1, '2026-11-01 09:00'), (1, '2026-…

👍7🔥6❤2🥰1

4 Nov 2026, 15:33 UTC≈2,490 views22 reactionsread 11 November 2026

🖥️ SQL-задача с подвохом: почему COUNT(*) считает неправильно? Даже опытные разработчики иногда ошибаются с оконными функциями PostgreSQL. Есть таблица событий: CREATE TABLE events ( id INT PRIMARY KEY, user_id INT, ts TIMESTAMP ); INSERT INTO events VALUES (1, 10, '2026-01-01 10:00'), (2, 10, '2026-01-01 10:05'), (3, 10, '2026-01-01 10:05'), (4, 10, '2026-01-01 10:20'); Выполняем запрос: SELECT …

👍13❤5🔥4

4 Nov 2026, 13:33 UTC≈2,170 views10 reactionsread 11 November 2026
Photo

🖥️ Черная пятница на Stepik на один из лучших курсов по контейнеризации! Если давно хотел разобраться в теме, но постоянно откладывал или терялся среди десятков материалов, этот курс на Stepik поможет выстроить обучение последовательно. Что получишь: - Понятные объяснения без лишней воды. - Практические задания для закрепления знаний. - Возможность учиться в удобном темпе. - Структурированный подход вместо хаотично…

❤3👍3👎2🔥2

3 Nov 2026, 12:02 UTC≈2,480 views14 reactionsread 11 November 2026
Photo

ORM превратила один SQL-запрос в 51. Разработчик даже не заметил Знакомая ситуация: код выглядит чисто, никаких SQL-запросов вручную, всё через ORM. Например, в Django: posts = Post.objects.all()[:50] for post in posts: print(post.author.name) Кажется, что мы просто получаем 50 постов с авторами. Но на практике это может вызвать 51 запрос к базе данных. Один запрос загружает посты, а ещё 50 отдельно получ…

👍7❤4🔥2😁1

1 Nov 2026, 09:48 UTC≈2,880 views18 reactionsread 11 November 2026

SQL-ловушка: этот UPDATE может незаметно испортить данные в продакшене Код корректный, PostgreSQL не выдаст ошибку. Но результат не так очевиден. Есть таблица товаров: CREATE TABLE products ( id INT PRIMARY KEY, price INT ); INSERT INTO products VALUES (1, 100); Применяем скидки: WITH discounts(id, amount) AS ( VALUES (1, 10), (1, 20) ) UPDATE products p SET price = p.price - d.amount FROM discou…

👍11❤6🔥1

31 Oct 2026, 18:47 UTC≈2,560 views14 reactionsread 11 November 2026
Forwarded from @ai_machinelearning_big_dataPhoto

✔️ RTX 5080 пропал из официального магазина NVIDIA Вслед за флагманской RTX 5090 из каталога маркетплейса NVIDIA в США пропала видеокарта RTX 5080. Оригинальная модель с 16 ГБ больше не отображается в фильтрах поиска, хотя на сайте по-прежнему указана ее стартовая цена в $999. Фактически же купить ускоритель за эти деньги было крайне сложно - у крупных ритейлеров минимальный прайс давно зафиксировался на уровне $2…

❤5👍3👎3🔥3

31 Oct 2026, 15:25 UTC≈2,670 views1 reactionsread 11 November 2026
Photo

💼 Войти в ИБ можно начать сегодня вечером, с телефона Не обязательно бросать работу и покупать курс за сотни тысяч, чтобы понять, твоё ли это. Начать можно с бесплатного мини-курса! ➡️ Начать в Telegram За пару часов разберёшься, чем вообще занимаются в кибербезопасности: что защищают, как работают атаки, как устроена защита и какие есть профессии с их зарплатами. Открывается в мессенджере, проходится по дороге с р…

👍1

28 Oct 2026, 08:30 UTC≈3,310 views12 reactionsread 11 November 2026
Photo

Один CVE - три уязвимости: раскрыты детали взлома Oracle PeopleSoft, которым пользовалась ShinyHunters. Исследователи ZDI выяснили, что за CVE-2026-35273 с оценкой CVSS 9.8 скрываются три ошибки в двух компонентах PeopleSoft. Начало цепочки – SSRF: атакующий заставляет сервер отправить запрос к собственному внутреннему интерфейсу управления. Этот интерфейс по умолчанию доверяет обращениям с 127.0.0.1. Поэтому внеш…

🔥5❤4👍3

26 Oct 2026, 18:38 UTC≈3,800 views19 reactionsread 11 November 2026
Photo

Microsoft предложит до 60 тысячам сотрудников добровольно уйти с компенсацией. Программа охватит подходящих под условия сотрудников в США, Великобритании, Канаде и Индии, сообщает The Verge. Среди участвующих направлений – Copilot, CoreAI, Windows + Devices, Xbox, финансы и HR. Некоторые подразделения участвуют частично, а маркетинг, коммерческий бизнес и безопасность исключены. Компания предлагает финансовую подд…

🤬8🔥6🥰3👍2

25 Oct 2026, 12:03 UTC≈3,220 views2 reactionsread 11 November 2026
Video

Пишешь «научи меня SQL»: Claude собирает персональный аудиокурс со ссылками на источники. Claudemy - open-source навык для Claude Code, который превращает выбранную тему примерно в 12 двухминутных уроков в формате разговора двух ведущих. Как это работает: - Изучает 20–40 страниц: документацию, практические материалы и альтернативные мнения. - Сопоставляет источники и отмечает, где они расходятся. - Создаёт пробный…

❤1👍1

Showing the 12 most recent of 112 posts we hold for @sqlhub. 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.

Posts recorded as deleted after publishing

We recorded 2 posts on @sqlhub as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.

A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.

First seen missing
1 September 2026
Most recent seen missing
2 October 2026
Median time before seen missing
5 days
Seen missing in the last 30 days
0

Polls

The 6 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.

23 Oct 2026, 11:05 UTCAnonymous Quiz467 voters

Какая команда в PostgreSQL используется для установки дополнительных модулей, таких как pg_stat_statements или postgis?

  1. CREATE EXTENSION47%
  2. LOAD MODULE18%
  3. INSTALL PACKAGE25%
  4. IMPORT PLUGIN10%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

20 Oct 2026, 09:52 UTCAnonymous Quiz640 voters

Какой оператор используется в PostgreSQL для проверки, содержит ли левый массив в себе все элементы правого массива?

  1. IN42%
  2. @>29%
  3. <@17%
  4. &&13%

Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.

28 Sept 2026, 16:06 UTCAnonymous Quiz477 voters

Для чего используется команда ANALYZE в PostgreSQL?

  1. Для проверки целостности файлов7%
  2. Для удаления неиспользуемых индексов6%
  3. Для дефрагментации таблиц3%
  4. Для сбора статистики о распределении данных84%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

16 Sept 2026, 20:10 UTCAnonymous Quiz446 voters

Какой объект в PostgreSQL используется для нормализации слов (удаления окончаний) при создании поискового индекса tsvector?

  1. Parser15%
  2. Dictionary23%
  3. Lexer30%
  4. Tokenizer31%

Shares as published, totalling 99%. No per-option vote count is published by Telegram, so none is shown.

23 Aug 2026, 16:40 UTCAnonymous Quiz489 voters

Как называется механизм PostgreSQL, позволяющий ограничить видимость строк в таблице для пользователя на основе определенных правил (политик)?

  1. Column-Level Security8%
  2. Table Access Control16%
  3. View-Only Access11%
  4. Row-Level Security (RLS)65%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

16 Jul 2026, 16:03 UTCAnonymous Quiz523 voters

Какой параметр в postgresql.conf задает объем общей памяти, используемой сервером для кэширования блоков данных?

  1. shared_buffers53%
  2. temp_buffers22%
  3. work_mem21%
  4. max_connections4%

Shares as published. 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 112 most recent posts we hold, published 15 July 2026 to 10 November 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.

Forward network

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.

Mentions

Named by 54 registered channels — 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.

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.

Channels Telegram recommends alongside this one

Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.

Анализ данных (Data analysis)
@data_analysis_ml · 51,923
#1
Machinelearning
@ai_machinelearning_big_data · 275,659
#2
Математика Дата саентиста
@data_math · 14,419
#3
Python/ django
@pythonl · 58,287
#4
DevOps
@DevOPSitsec · 23,892
#5
Big Data AI
@bigdatai · 18,329
#6
Machine learning Interview
@machinelearning_interview · 30,560
#7
Python вопросы с собеседований
@python_job_interview · 24,906
#8
Машинное обучение RU
@machinelearning_ru · 18,339
#9
Linux Academy
@linuxacademiya · 28,647
#10
Data Science
@datascienceiot · 42,496
#11
Data Secrets
@data_secrets · 96,035
#12
Data Science Jobs
@datascienceml_jobs · 21,642
#13
Инжиниринг Данных
@rockyourdata · 23,685
#14
Аналитик данных
@dataanlitics · 6,386
#15
Искусственный интеллект. Высокие технологии
@vistehno · 70,139
#16
Python RU
@pro_python_code · 12,302
#17
Машиннное обучение | Наука о данных Библиотека
@machinelearning_books · 16,955
#18
Библиотека С# С++
@cpluscsharp · 10,015
#19
LEFT JOIN
@leftjoin · 41,485
#20
C# (C Sharp) programming
@csharp_ci · 17,963
#21
Python Jobs
@python_djangojobs · 15,125
#22
Reveal the Data
@revealthedata · 27,678
#23
Data Science | Machinelearning [ru]
@devsp · 19,659
#24
Javascript
@javascriptv · 16,664
#25
Rust
@rust_code · 9,152
#26
Neural Networks | Нейронные сети
@neural · 11,724
#27
Библиотека дата-сайентиста | Data Science, Machine learning, анализ данных, машинное обучение
@dsproglib · 18,290
#28
Datalytics
@datalytx · 8,783
#29
Artificial Intelligence
@ArtificialIntelligencedl · 16,815
#30
Data jobs — вакансии по data science, анализу данных, аналитике, искусственному интеллекту
@datajob · 15,139
#31
Golang Books
@golang_books · 16,863
#32
Библиотека программиста
@proglibrary · 77,612
#33
Golang вопросы собеседований
@golang_interview · 15,018
#34
IT Portal
@IT_Portal · 119,243
#35
Хабр
@habr_com · 134,497
#36
No Data No Growth | Pavel Bukhtik
@nodatanogrowth · 12,776
#37
SQLpedia | Базы данных
@sql_wiki · 5,913
#38
Data engineer / SQL работа
@datascjobs · 5,740
#39
Data jobs feed
@datajobschannel · 12,625
#40
Данные на стероидах
@sterodata · 3,258
#41
Базы данных | Access, SQL, Big Data
@databases_secrets · 30,012
#42
BZD • Книги для программистов
@bzd_channel · 36,213
#43
Python Developer
@python_tg · 21,216
#44
Нескучный Data Science
@not_boring_ds · 12,081
#45
Аналитика данных / Data Study
@data_study · 9,414
#46
Библиотека задач по Data Science | тесты, код, задания
@ds_problems_lib · 3,966
#47
Start Career in DS
@start_ds · 11,463
#48
Github
@github_code · 2,548
#49
Библиотека питониста | Python, Django, Flask
@pyproglib · 36,972
#50
Java Books
@java_library · 14,048
#51
DeepSchool
@deep_school · 10,723
#52
Yandex for ML
@yandexforml · 19,136
#53
data.csv
@data_csv · 13,773
#54
Машинное обучение. Книги по программированию
@maschinelearning · 10,849
#55
karpov.courses
@KarpovCourses · 27,313
#56
Библиотека собеса по Data Science | вопросы с собеседований
@ds_interview_lib · 4,459
#57
Golang
@Golang_google · 40,453
#58
Kali Linux
@linuxkalii · 55,842
#59
Python tests
@python_testit · 6,872
#60
C++ Academy
@cpluspluc · 15,457
#61
Java
@javatg · 16,563
#62
PHP Academy
@phpshka · 9,131
#63
C# 1001 notes
@csharp_1001_notes · 6,673
#64
Английский для программистов
@english_forprogrammers · 8,237
#65
эйай ньюз
@ai_newz · 98,262
#66
Время Валеры
@cryptovalerii · 32,082
#67
Django Python
@Django_pythonl · 6,573
#68
Physics.Math.Code
@physics_lib · 146,676
#69
Сиолошная
@seeallochnaya · 81,254
#70
настенька и графики
@nastengraph · 28,082
#71
Denis Sexy IT 🤖
@denissexy · 140,753
#72
IT мемы | Мемы программиста
@memes_prog · 6,220
#73
Love. Death. Transformers.
@lovedeathtransformers · 26,252
#74
CodeCamp
@codecamp · 177,629
#75
[PYTHON:TODAY]
@python2day · 63,348
#76
XOR
@xor_journal · 195,549
#77
GitHub Community
@github · 154,995
#78
Зарплатник Аналитика
@zarplatnik_analytics · 11,694
#79
React JS
@react_tg · 16,049
#80
Простой Python | Программирование
@python_piton_javascript · 123,691
#81
Поступашки - ШАД, Стажировки и Магистратура
@postypashki_old · 47,200
#82
Job for Analysts & Data Scientists
@foranalysts · 37,857
#83
Дата-сторителлинг
@data_publication · 11,916
#84
Young&&Yandex
@Young_and_Yandex · 112,989
#85
Мобильная разработка
@mobdevelop · 3,841
#86
Библиотека Go-разработчика | Golang
@goproglib · 23,896
#87

Read from Telegram’s recommendation API, most recently 2 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Linux Academy
@linuxacademiya · 28,647
Telegram ranks this channel #4 of 84 here — alongside 83 others — read 9 September 2026
Анализ данных (Data analysis)
@data_analysis_ml · 51,923
Telegram ranks this channel #4 of 93 here — alongside 92 others — read 25 August 2026
DevOps
@DevOPSitsec · 23,892
Telegram ranks this channel #5 of 90 here — alongside 89 others — read 18 September 2026
Python вопросы с собеседований
@python_job_interview · 24,906
Telegram ranks this channel #6 of 90 here — alongside 89 others — read 15 September 2026
Python/ django
@pythonl · 58,287
Telegram ranks this channel #6 of 84 here — alongside 83 others — read 22 August 2026
Искусственный интеллект. Высокие технологии
@vistehno · 70,139
Telegram ranks this channel #7 of 94 here — alongside 93 others — read 20 August 2026
Базы данных | Access, SQL, Big Data
@databases_secrets · 30,012
Telegram ranks this channel #11 of 82 here — alongside 81 others — read 7 September 2026
Data Science
@datascienceiot · 42,496
Telegram ranks this channel #11 of 76 here — alongside 75 others — read 29 August 2026
Data Science Jobs
@datascienceml_jobs · 21,642
Telegram ranks this channel #22 of 97 here — alongside 96 others — read 24 September 2026
Секреты аналитики | Data Science, BI, Tableau
@analytics_secrets · 46,814
Telegram ranks this channel #25 of 85 here — alongside 84 others — read 27 August 2026
Data Science | Machinelearning [ru]
@devsp · 19,659
Telegram ranks this channel #26 of 91 here — alongside 90 others — read 30 September 2026
Machinelearning
@ai_machinelearning_big_data · 275,659
Telegram ranks this channel #30 of 95 here — alongside 94 others — read 10 August 2026
Machine learning Interview
@machinelearning_interview · 30,560
Telegram ranks this channel #36 of 98 here — alongside 97 others — read 7 September 2026
Python Learning
@Python_per_month · 27,879
Telegram ranks this channel #42 of 86 here — alongside 85 others — read 9 September 2026
LEFT JOIN
@leftjoin · 41,485
Telegram ranks this channel #43 of 95 here — alongside 94 others — read 29 August 2026
Python Books. Книги по питону
@pythonbooks · 38,331
Telegram ranks this channel #48 of 65 here — alongside 64 others — read 17 September 2026
Инжиниринг Данных
@rockyourdata · 23,685
Telegram ranks this channel #51 of 93 here — alongside 92 others — read 17 September 2026
Python Hacks
@python_secrets · 40,332
Telegram ranks this channel #54 of 82 here — alongside 81 others — read 30 August 2026
Golang
@Golang_google · 40,453
Telegram ranks this channel #56 of 90 here — alongside 89 others — read 30 August 2026
Kali Linux
@linuxkalii · 55,842
Telegram ranks this channel #56 of 89 here — alongside 88 others — read 23 August 2026
Python обучающий
@pythonist24 · 55,221
Telegram ranks this channel #58 of 88 here — alongside 87 others — read 23 August 2026
Библиотека питониста | Python, Django, Flask
@pyproglib · 36,972
Telegram ranks this channel #65 of 84 here — alongside 83 others — read 1 September 2026
Библиотека программиста
@proglibrary · 77,612
Telegram ranks this channel #66 of 82 here — alongside 81 others — read 19 August 2026
Простой Python | Программирование
@python_piton_javascript · 123,691
Telegram ranks this channel #68 of 84 here — alongside 83 others — read 13 August 2026

This channel appears in 26 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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 10 November 2026 — this entry's latest reading, not the date you are reading this.

“Data Science. SQL hub” (@sqlhub), 36,025 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/sqlhub.

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.