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Channel

Data Science. SQL hub

@sqlhub

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

35,960subscribers

+80 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 live25 September 2026
Measurements held33
Confirmed unchanged1 time, most recently 25 September 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 why it has no browse page of its own yet.

Growth

35,85435,98835,9216 August 2026 — 35,880 subscribers6 August 2026 — 35,886 subscribers7 August 2026 — 35,894 subscribers8 August 2026 — 35,892 subscribers9 August 2026 — 35,889 subscribers10 August 2026 — 35,888 subscribers11 August 2026 — 35,898 subscribers12 August 2026 — 35,886 subscribers13 August 2026 — 35,877 subscribers14 August 2026 — 35,881 subscribers16 August 2026 — 35,864 subscribers17 August 2026 — 35,870 subscribers18 August 2026 — 35,872 subscribers19 August 2026 — 35,854 subscribers20 August 2026 — 35,860 subscribers21 August 2026 — 35,873 subscribers23 August 2026 — 35,924 subscribers25 August 2026 — 35,928 subscribers26 August 2026 — 35,916 subscribers28 August 2026 — 35,903 subscribers29 August 2026 — 35,909 subscribers29 August 2026 — 35,921 subscribers31 August 2026 — 35,943 subscribers1 September 2026 — 35,971 subscribers3 September 2026 — 35,984 subscribers4 September 2026 — 35,988 subscribers8 September 2026 — 35,971 subscribers11 September 2026 — 35,955 subscribers13 September 2026 — 35,946 subscribers14 September 2026 — 35,966 subscribers16 September 2026 — 35,983 subscribers18 September 2026 — 35,969 subscribers25 September 2026 — 35,960 subscribers35,9606 August 202625 September 2026
33 measurements spanning 50 days, net +80. 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 35,834–36,008 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)SubscribersChange
25 Sept 2026, 08:0235,960-9
18 Sept 2026, 18:5635,969-14
16 Sept 2026, 07:5935,983+17
14 Sept 2026, 16:1935,966+20
13 Sept 2026, 01:2235,946-9
11 Sept 2026, 02:5635,955-16
8 Sept 2026, 07:3535,971-17
4 Sept 2026, 23:3835,988+4
3 Sept 2026, 05:5735,984+13
1 Sept 2026, 21:4635,971+28
31 Aug 2026, 20:2635,943+22
29 Aug 2026, 21:2635,921+12
29 Aug 2026, 00:1435,909+6
28 Aug 2026, 01:3335,903-13
26 Aug 2026, 01:0335,916-12
25 Aug 2026, 01:1735,928+4
23 Aug 2026, 15:5435,924+51
21 Aug 2026, 22:2835,873+13
20 Aug 2026, 17:4235,860+6
19 Aug 2026, 16:2735,854first reading

Engagement

69 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 89 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
8.19%
avg views ÷ 35,960 subscribers
Avg views / post
2,950
25 posts measured
Reaction rate
0.53%
reactions ÷ views · ER floor
Posts in window
25
of 69 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 24 of 25 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 25 September 2026
Posts held69 (15 July 2026 – 25 September 2026)
Views total73,670
Reactions total382
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken27 Sept 2026, 04:50 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
≈1,170
Videos
≈99
Links
≈1,180

Lifetime counters from Telegram’s own channel header, read 27 September 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
4m 24s
Average length
44s

Measured directly from 6 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

951 reactions across 64 posts, in 12 distinct kinds. The most used accounts for 36.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍34836.6%
❤29731.2%
🔥19120.1%
😁343.58%
👎242.52%
🥰181.89%
😱151.58%
🎉60.631%
👏60.631%
🤔60.631%
🤬40.421%
🤯20.21%

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 68 of the 69 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 974 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 69 most recent posts we hold, published 15 July 2026 to 25 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.

Advertising

Ad load
8.70%
6 of 69 posts carry an ad marker
Regulatory tokens
6
posts carrying an erid · 5 distinct tokens
Median views · ads
2,120
over 6 measured posts
Median views · rest
3,090
over 63 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
2Vtzqx3mtnf120 August 202620 August 2026
2W5zFGPtHER116 July 202616 July 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 69 most recent posts we hold, published 15 July 2026 to 25 September 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

25 Sept 2026, 09:00 UTC≈1,440 views6 reactionsread 27 September 2026
Photo

Тысячи ИИ-агентов одновременно читают продакшен-базу. Что происходит с PostgreSQL? Google представила PostgreSQL for agents в AlloyDB. Когда нагрузка растёт, система за секунды запускает изолированные экземпляры базы для агентов. Они получают доступ на чтение к актуальным данным, но не конкурируют за вычислительные ресурсы с основной базой. После работы экземпляры масштабируются до нуля. Агентам доступны SQL, индек…

🔥3❤2👍1

24 Sept 2026, 10:40 UTC≈1,690 views3 reactionsread 27 September 2026
Video

Softmax простыми словами: что значат 66,5% в ответе нейросети? Softmax простыми словами: ChatGPT выдаёт не ответы, а вероятности следующих токенов, и 66,5% означают только то, что такое продолжение текста самое вероятное. Модель может звучать уверенно и при этом ошибаться, потому что вероятность токена это не вероятность правды. Разбираем на деле Киры, как проверять ответы ИИ через источники и контекст.

❤1👍1🔥1

24 Sept 2026, 09:10 UTC≈1,640 viewsread 27 September 2026

🔥Один слой данных вместо цепочки копий между системами В традиционной аналитической инфраструктуре результаты обработки приходится переносить между хранилищем, SQL-системой и BI. Вместе с каждой копией появляется новая задача: ее нужно обновлять, сверять с исходными данными и учитывать в правилах доступа. В DataLens Platform разные инструменты работают с общей основой данных. Lakehouse построен на S3 и Apache Icebe…

23 Sept 2026, 09:58 UTC≈1,780 views17 reactionsread 27 September 2026

⚡️ SQL-задача с опасным подвохом Какой баланс получит аккаунт после выполнения запроса в PostgreSQL? CREATE TABLE accounts ( id int PRIMARY KEY, balance int ); CREATE TABLE operations ( account_id int, amount int ); INSERT INTO accounts VALUES (1, 100); INSERT INTO operations VALUES (1, 10), (1, 20); UPDATE accounts a SET balance = a.balance + o.amount FROM operations o WHERE o.…

👍12❤3🥰2

22 Sept 2026, 15:39 UTC≈1,460 views5 reactionsread 27 September 2026
Forwarded from @ai_machinelearning_big_data

🌟 Samsone: открытые аудиоязыковые модели для смартфонов Samsung опубликовали Samsone - семейство из трёх небольших аудиоязыковых моделей для работы на мобильных устройствах: Samsone-99M, Samsone-134M и Samsone-356M. Проект будет участвовать в конференции Interspeech 2026, которая пройдет с 27 сентября по 1 октября в Сиднее. Модели принимают один или несколько аудиофрагментов вместе с текстовым запросом и отвечают …

❤2👍1👏1🔥1

22 Sept 2026, 10:45 UTC≈1,730 views3 reactionsread 27 September 2026
Photo

Объектное хранилище в эпоху быстрых данных Объём данных, с которыми нужно работать, растёт ежедневно. Стандартных решений уже не хватает для задач ИИ и аналитики. Большие объёмы данных нужно не только хранить, но и быстро записывать и читать. В MWS Cloud Platform мы построили объектное хранилище не только на привычных HDD-дисках, но и на NVMe. На вебинаре покажем, какие сценарии работы это открывает и как меняет пр…

❤2👍1

21 Sept 2026, 09:30 UTC≈2,180 views7 reactionsread 27 September 2026

🧩 Сложная SQL-задача: симуляция DNS-кеша Есть таблица запросов: CREATE TABLE dns_requests ( request_id BIGINT PRIMARY KEY, requested_at TIMESTAMP, node_id INT, domain TEXT, record_type TEXT, ttl_seconds INT ); Правила: • Ключ кеша: node_id + domain + record_type. • Первый запрос - MISS, он создаёт запись в кеше. • Запись действует до requested_at + ttl_seconds. • Запрос в момент истечения…

👍4❤3

18 Sept 2026, 12:04 UTC≈2,890 views5 reactionsread 27 September 2026
Photo

🔥 PostgreSQL 19 задерживается релиз может сдвинуться на несколько недель или даже месяцев. Причина не в одной критической ошибке, а в масштабе переработок. После начала бета-тестирования из PostgreSQL 19 уже откатили 53 изменения, включая несколько заметных функций. Из релиза убрали SQL/PGQ для графовых запросов, GROUP BY ALL, объединение и разделение партиций через ALTER TABLE, онлайн-переключение checksums, част…

👍5

17 Sept 2026, 15:56 UTC≈2,670 views5 reactionsread 27 September 2026
Advertisementerid 2VSb5xkQt6EPhoto

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👍3👏1🤬1

17 Sept 2026, 07:24 UTC≈2,160 views10 reactionsread 27 September 2026
Forwarded from @ai_machinelearning_big_dataPhoto

📌 NY Post: Anthropic - это культ Профессор Вашингтонского университета Педро Домингос в интервью New York Post рассказал, что сотрудники Anthropic относятся к Claude как к человеку - приписывают модели мотивы, эмоции, намерения и некоторую степень сознания. Домингос много лет знаком с Дарио Амодеи и её ведущими инженерами. Культуру Anthropic он назвал сектантской и связал это с наймом. По его словам, компания отбир…

👍3🤔3❤2🔥2

16 Sept 2026, 20:10 UTC≈2,180 views8 reactionsread 27 September 2026
Poll

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.

👍6❤2

16 Sept 2026, 18:02 UTC≈2,160 views9 reactionsread 27 September 2026
Photo

Стать специалистом по Data Science всего за 10 недель — это реально! Если давно смотрите в сторону Data Science, но откладываете старт из-за огромного количества технологий, математики и непонятного пути до первой работы — сейчас можно зайти в профессию по-другому. Симулейтив запускает интенсивный буткемп по Data Science, который построен вокруг главного: за первые 10 недель собрать необходимый стек, получить практ…

👍3😁3👎2❤1

Showing the 12 most recent of 69 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.

Polls

The 3 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.

16 Sept 2026, 20:10 UTCAnonymous Quiz434 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 69 most recent posts we hold, published 15 July 2026 to 25 September 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

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.

Mentions

Named by 50 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.

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@datajobschannel · 12,272
#40
Данные на стероидах
@sterodata · 3,248
#41
Базы данных | Access, SQL, Big Data
@databases_secrets · 30,002
#42
BZD • Книги для программистов
@bzd_channel · 36,430
#43
Python Developer
@python_tg · 20,963
#44
Нескучный Data Science
@not_boring_ds · 12,052
#45
Аналитика данных / Data Study
@data_study · 9,465
#46
Библиотека задач по Data Science | тесты, код, задания
@ds_problems_lib · 3,988
#47
Start Career in DS
@start_ds · 11,495
#48
Github
@github_code · 2,529
#49
Библиотека питониста | Python, Django, Flask
@pyproglib · 37,384
#50
Java Books
@java_library · 14,222
#51
DeepSchool
@deep_school · 10,738
#52
Yandex for ML
@yandexforml · 18,854
#53
data.csv
@data_csv · 13,839
#54
Машинное обучение. Книги по программированию
@maschinelearning · 10,823
#55
karpov.courses
@KarpovCourses · 27,446
#56
Библиотека собеса по Data Science | вопросы с собеседований
@ds_interview_lib · 4,466
#57
Golang
@Golang_google · 40,461
#58
Kali Linux
@linuxkalii · 55,412
#59
Python tests
@python_testit · 6,894
#60
C++ Academy
@cpluspluc · 15,536
#61
Java
@javatg · 16,748
#62
PHP Academy
@phpshka · 9,245
#63
C# 1001 notes
@csharp_1001_notes · 6,651
#64
Английский для программистов
@english_forprogrammers · 8,268
#65
эйай ньюз
@ai_newz · 96,889
#66
Время Валеры
@cryptovalerii · 30,808
#67
Django Python
@Django_pythonl · 6,611
#68
Physics.Math.Code
@physics_lib · 146,712
#69
Сиолошная
@seeallochnaya · 79,594
#70
настенька и графики
@nastengraph · 28,213
#71
Denis Sexy IT 🤖
@denissexy · 137,325
#72
IT мемы | Мемы программиста
@memes_prog · 6,262
#73
Love. Death. Transformers.
@lovedeathtransformers · 25,677
#74
CodeCamp
@codecamp · 181,043
#75
[PYTHON:TODAY]
@python2day · 63,764
#76
XOR
@xor_journal · 182,317
#77
GitHub Community
@github · 155,991
#78
Зарплатник Аналитика
@zarplatnik_analytics · 11,546
#79
React JS
@react_tg · 16,279
#80
Простой Python | Программирование
@python_piton_javascript · 126,249
#81
Поступашки - ШАД, Стажировки и Магистратура
@postypashki_old · 45,531
#82
Job for Analysts & Data Scientists
@foranalysts · 36,643
#83
Дата-сторителлинг
@data_publication · 11,933
#84
Young&&Yandex
@Young_and_Yandex · 111,329
#85
Мобильная разработка
@mobdevelop · 3,882
#86
Библиотека Go-разработчика | Golang
@goproglib · 24,076
#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 · 28,434
Telegram ranks this channel #4 of 84 here — alongside 83 others — read 9 September 2026
Анализ данных (Data analysis)
@data_analysis_ml · 50,656
Telegram ranks this channel #4 of 93 here — alongside 92 others — read 25 August 2026
DevOps
@DevOPSitsec · 23,684
Telegram ranks this channel #5 of 90 here — alongside 89 others — read 18 September 2026
Python вопросы с собеседований
@python_job_interview · 24,881
Telegram ranks this channel #6 of 90 here — alongside 89 others — read 15 September 2026
Python/ django
@pythonl · 58,866
Telegram ranks this channel #6 of 84 here — alongside 83 others — read 22 August 2026
Искусственный интеллект. Высокие технологии
@vistehno · 71,491
Telegram ranks this channel #7 of 94 here — alongside 93 others — read 20 August 2026
Базы данных | Access, SQL, Big Data
@databases_secrets · 30,002
Telegram ranks this channel #11 of 82 here — alongside 81 others — read 7 September 2026
Data Science
@datascienceiot · 42,634
Telegram ranks this channel #11 of 76 here — alongside 75 others — read 29 August 2026
Data Science Jobs
@datascienceml_jobs · 21,227
Telegram ranks this channel #22 of 97 here — alongside 96 others — read 24 September 2026
Секреты аналитики | Data Science, BI, Tableau
@analytics_secrets · 46,900
Telegram ranks this channel #25 of 85 here — alongside 84 others — read 27 August 2026
Machinelearning
@ai_machinelearning_big_data · 279,417
Telegram ranks this channel #30 of 95 here — alongside 94 others — read 10 August 2026
Machine learning Interview
@machinelearning_interview · 30,308
Telegram ranks this channel #36 of 98 here — alongside 97 others — read 7 September 2026
Python Learning
@Python_per_month · 28,238
Telegram ranks this channel #42 of 86 here — alongside 85 others — read 9 September 2026
LEFT JOIN
@leftjoin · 42,064
Telegram ranks this channel #43 of 95 here — alongside 94 others — read 29 August 2026
Python Books. Книги по питону
@pythonbooks · 38,517
Telegram ranks this channel #48 of 65 here — alongside 64 others — read 17 September 2026
Инжиниринг Данных
@rockyourdata · 23,732
Telegram ranks this channel #51 of 93 here — alongside 92 others — read 17 September 2026
Python Hacks
@python_secrets · 40,594
Telegram ranks this channel #54 of 82 here — alongside 81 others — read 30 August 2026
Golang
@Golang_google · 40,461
Telegram ranks this channel #56 of 90 here — alongside 89 others — read 30 August 2026
Kali Linux
@linuxkalii · 55,412
Telegram ranks this channel #56 of 89 here — alongside 88 others — read 23 August 2026
Python обучающий
@pythonist24 · 55,872
Telegram ranks this channel #58 of 88 here — alongside 87 others — read 23 August 2026
Библиотека питониста | Python, Django, Flask
@pyproglib · 37,384
Telegram ranks this channel #65 of 84 here — alongside 83 others — read 1 September 2026
Библиотека программиста
@proglibrary · 78,288
Telegram ranks this channel #66 of 82 here — alongside 81 others — read 19 August 2026
Простой Python | Программирование
@python_piton_javascript · 126,249
Telegram ranks this channel #68 of 84 here — alongside 83 others — read 13 August 2026
Клуб анонимных аналитиков
@analyst_club · 33,554
Telegram ranks this channel #85 of 96 here — alongside 95 others — read 4 September 2026

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

“Data Science. SQL hub” (@sqlhub), 35,960 subscribers as measured 25 September 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.