Telegram RegisterThe public register of Telegram

Channel

Pangolin Community

@pangolindb

On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry

2,714subscribers

-10 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1002073759237
TypeChannel
Username@pangolindb
CreatedBetween 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/pangolindb

Growth

2,7142,7242,7196 August 2026 — 2,724 subscribers7 August 2026 — 2,721 subscribers12 August 2026 — 2,714 subscribers6 August 202612 August 2026
3 measurements spanning 6 days, net -10. 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 2,713–2,726 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 21:282,714-7
7 Aug 2026, 03:542,721-3
6 Aug 2026, 19:482,724first reading

Engagement

8 posts held, back to 9 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 2 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
25.8%
avg views ÷ 2,714 subscribers
Avg views / post
701
7 posts measured
Reaction rate
1.47%
reactions ÷ views · ER floor
Posts in window
7
of 8 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 6 August 2026
Posts held8 (9 July 20266 August 2026)
Views total4,910
Reactions total72
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 16:13 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.

Reaction mix

95 reactions across 8 posts, in 11 distinct kinds. The most used accounts for 22.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍2122.1%
custom 51953043337296158641920.0%
🔥1920.0%
1111.6%
custom 519304179220272042766.32%
custom 536618361910044718466.32%
custom 519296505831701193655.26%
😍55.26%
custom 533033750851540235211.05%
😁11.05%
🤔11.05%

Custom emoji. 5 of the rows above are 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 counts beside them areTelegram’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 8 of the 8 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 95reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 8 most recent posts we hold, published 9 July 2026 to 6 August 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

6 Aug 2026, 11:02 UTC474 views9 reactionsread 7 August 2026
Photo

Анонс от команды Pangolin 🔔 Мы запускаем серию технических вебинаров, где разберём три ключевые темы, которые касаются каждого, кто работает с СУБД. Без воды, без маркетинга — только практика, демонстрации и ответы на ваши вопросы. Когда? 🔹 25 августа в 11:00 Авторизация через MS AD: как сэкономить и упростить, обезопасив процесс эксплуатации в like-Postgres СУБД, на примере Pangolin 🔹 15 сентября в 11:00 Диагнос

custom 51930417922027204275👍31

3 Aug 2026, 08:32 UTC546 views6 reactionsread 7 August 2026
Photo

Защищённый обмен данными на высокой нагрузке: Pangolin DB совместима с MFlash СберТех и МСофт подтвердили совместимость решений: СУБД Pangolin стабильно работает в связке с платформой защищённого файлового обмена MFlash. MFlash — корпоративная платформа для безопасной передачи файлов любого размера внутри компании и с внешними контрагентами, с обязательным применением политик ИБ на каждом шаге. Лабораторные испыта

custom 51953043337296158643👍2🔥1

30 Jul 2026, 09:15 UTC709 views7 reactionsread 7 August 2026
Photo

Новые горизонты для классных специалистов! Мы знаем, что качественные продукты создают крутые люди, поэтому мы всегда рады сильным умам, которые ищут не просто «работу», а интересные вызовы и надежную команду. Если вы сейчас в поиске или просто думаете о следующих шагах в карьере — приходите к нам! Кого мы сейчас ищем: ➡️ DevOps (Pangolin) ➡️ С разработчик (Pangolin) ➡️ DBA администратор баз данных (Pangolin)

🔥3👍2custom 51930417922027204271custom 51953043337296158641

24 Jul 2026, 08:31 UTC871 views14 reactionsread 7 August 2026
Photo

Platform V DataGrid и Pangolin DB: двукратное ускорение обработки данных в 1С Год назад специалисты AUXO проверяли производительность Pangolin DB. Сегодня еще одна СУБД от СберТеха — Platform V DataGrid — успешно прошла нагрузочные испытания 👌 Интегратор тестировал связку с «1С:Предприятие 8.3» в сценариях комбинированной загрузки, используя DataGrid как оперативный буфер для предобработки данных. В роли основного

5custom 51953043337296158643👍2🔥2🤔1😁1

20 Jul 2026, 09:59 UTC765 views6 reactionsread 7 August 2026
Forwarded from @platformvnewsPhoto

Новые правила игры на рынке российских СУБД В 2025 году рынок систем управления базами данных вырос более чем на 20%, а доля отечественных решений в новых проектах превысила 90%. Этап «экстренного импортозамещения» остался позади — сегодня бизнесу нужны не просто аналоги, а высокопроизводительные платформы с поддержкой 24/7. Простые миграционные кейсы уже реализованы, и теперь фокус смещается на более сложные задач

2👍2🔥2

16 Jul 2026, 09:00 UTC786 views8 reactionsread 7 August 2026
Photo

Готовый ПАК для ИИ-нагрузок СберТех и производитель оборудования «Норси-Транс» подтвердили совместимость решений: СУБД Pangolin DB и серверная ОС Platform V SberLinux OS Server отлично работают на инференс-серверах «Пантера AI». «Пантера AI» — специализированный вычислительный сервер для использования уже обученной модели в реальных приложениях и задачах бизнеса. Подходит для создания сервисов на базе больших языко

custom 519530433372961586432👍2🔥1

14 Jul 2026, 09:24 UTC759 views22 reactionsread 7 August 2026
Photo

Обновление Platform V CopyWala CopyWala продолжает развиваться, предлагая ИТ-командам более быстрые и надёжные инструменты для резервного копирования и восстановления баз данных. Команда продукта представляет релиз 1.3.0, ключевыми векторами которого стали поддержка корпоративных хранилищ Dell Data Domain, интеграция с СУБД Platform V Vector DB, защитное преобразование резервных копий (в том числе для баз с включен

👍7custom 53661836191004471846custom 51929650583170119365🔥3custom 53303375085154023521

9 Jul 2026, 12:20 UTC913 views23 reactionsread 7 August 2026
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Хобби айтишника: сквош — когда скорость мысли и тела сходятся в одной точке В ритме постоянных релизов, дедлайнов и сложных решений важно не забывать про перезагрузку. В новом выпуске рубрики #хоббиайтишника мы поговорили с Ариной Букреевой, лидером направления по управлению знаниями Pangolin. Её способ держать себя в тонусе — сквош 🎾 Казалось бы, что общего у ракеточного спорта и работы с контентом? Оказывается,

custom 51953043337296158649🔥7😍51👍1

Showing the 8 most recent of 8 posts we hold for @pangolindb. 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.

Citation-graph rank

Citation-graph rank — 151,020 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

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 3 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.

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Pangolin Community” (@pangolindb), 2,714 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/pangolindb.

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.