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PostgreSQL Pro | Database Mastery

@postgres

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

1,323subscribers

-2 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1002066913405
TypeChannel
Username@postgres
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 live29 August 2026
Measurements held9
Confirmed unchanged1 time, most recently 29 August 2026
On Telegramt.me/postgres

Growth

1,3201,3261,3237 August 2026 — 1,325 subscribers7 August 2026 — 1,325 subscribers10 August 2026 — 1,324 subscribers13 August 2026 — 1,320 subscribers16 August 2026 — 1,322 subscribers19 August 2026 — 1,321 subscribers23 August 2026 — 1,322 subscribers26 August 2026 — 1,326 subscribers29 August 2026 — 1,323 subscribers7 August 202629 August 2026
9 measurements spanning 22 days, net -2. 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 1,319–1,327 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
29 Aug 2026, 15:421,323-3
26 Aug 2026, 16:271,326+4
23 Aug 2026, 22:171,322+1
19 Aug 2026, 22:481,321-1
16 Aug 2026, 22:221,322+2
13 Aug 2026, 06:261,320-4
10 Aug 2026, 14:531,324-1
7 Aug 2026, 05:311,325no change
7 Aug 2026, 05:231,325first reading

Engagement

20 posts held, back to 10 March 2026the 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 5 July 2026. An engagement rate over an empty window would be a number about nothing.

Reaction mix

27 reactions across 8 posts, in 4 distinct kinds. The most used accounts for 66.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
1866.7%
🔥518.5%
👍311.1%
👏13.70%

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 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 27reactions 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 10 March 2026 to 5 July 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
25.0%
5 of 20 posts carry an ad marker
Regulatory tokens
0
none — marked by hashtag only
Median views · ads
554
over 4 measured posts
Median views · rest
566
over 12 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. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.

Measured over the 20 most recent posts we hold, published 10 March 2026 to 5 July 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

5 Jul 2026, 05:05 UTCviews —
Advertisement

PostgreSQL Pro | Database Mastery pinned «https://youtu.be/imBbqzIOQdo #ad»

1 Jul 2026, 20:04 UTCviews —

PostgreSQL Pro | Database Mastery pinned «Every RAG app, semantic search feature, and “related to this” button depends on one hidden operation: Find the nearest points among millions — fast. That sounds simple until you realize each document is stored as a high-dimensional vector, often with more…»

1 Jul 2026, 19:53 UTC554 viewsread 7 August 2026
Advertisement

Every RAG app, semantic search feature, and “related to this” button depends on one hidden operation: Find the nearest points among millions — fast. That sounds simple until you realize each document is stored as a high-dimensional vector, often with more than a thousand numbers. If your app has two million help articles, the brute-force approach means comparing the query against every single vector, every time. T

19 May 2026, 13:39 UTC885 views9 reactionsread 7 August 2026
Advertisement

Made an animated explainer on what actually happens when you go from no index to a B-tree index on a column. Hopefully useful for folks who are comfortable writing SQL but haven't dug into the execution side. The core comparison the video covers: Without index: - Database scans every row sequentially - Million-row table = up to 1 million comparisons - Roughly 500ms on typical hardware With B-tree index: - Database

7👍1🔥1

12 May 2026, 14:04 UTC857 views5 reactionsread 7 August 2026
Advertisement

"What happens when you type a URL into a browser?" is one of the most common technical interview questions. Most online answers cover DNS and TCP but skip everything that happens server-side — load balancers, reverse proxies, framework routing, database queries. I made an animated explainer that walks through the full path: browser → DNS → TCP → TLS → load balancer → reverse proxy → application server → controller →

3👍1🔥1

27 Mar 2026, 06:22 UTC≈1,240 views3 reactionsread 7 August 2026

📊 Week 10 done. Migrations without fear. This week: ✅ Monday — Why ALTER TABLE is terrifying (and doesn't have to be) ✅ Tuesday — Safe vs dangerous operations (know before you run) ✅ Wednesday — 💰 Complete migration system (3⭐) ✅ Thursday — Three levels of rollback The takeaway: every migration should have a written rollback plan before you run it. Takes 5 minutes. Saves you from the worst night of your career. -

1👍1🔥1

26 Mar 2026, 12:48 UTC942 views4 reactionsread 7 August 2026

🐌 Finding and fixing slow queries. The 80/20 approach. Step 1: Find the worst offenders. -- Enable if not already: -- ALTER SYSTEM SET shared_preload_libraries = 'pg_stat_statements'; -- Restart PostgreSQL. -- Top 5 by total time (these hurt your server the most) SELECT round(total_exec_time::numeric, 0) as total_ms, calls, round(mean_exec_time::numeric, 2) as avg_ms, left(query, 100) as query FROM

4

25 Mar 2026, 07:23 UTCviews —

PostgreSQL Pro | Database Mastery pinned «🔐 Complete Monitoring Dashboard — See Everything, Pay Nothing What's inside: 📦 COMPLETE SYSTEM (3 ⭐) 1. HEALTH CHECK VIEW - Single query returns overall database health score (0-100) - Cache hit ratio, connection usage, bloat, replication lag …»

24 Mar 2026, 07:25 UTC632 views2 reactionsread 7 August 2026

📊 5 queries. Run them once a week. Know exactly what's happening. QUERY 1: TABLE BLOAT AND SIZE SELECT relname as table_name, pg_size_pretty(pg_total_relation_size(oid)) as total_size, n_live_tup as live_rows, n_dead_tup as dead_rows, CASE WHEN n_live_tup > 0 THEN round(100.0 * n_dead_tup / n_live_tup, 1) ELSE 0 END as dead_pct FROM pg_stat_user_tables ORDER BY pg_total_relation_

2

23 Mar 2026, 09:33 UTC522 viewsread 7 August 2026

🔍 Your database is talking to you. You're just not listening. PostgreSQL collects stats on everything: - Which queries are slow - Which tables are bloated - Which indexes are never used - How much cache you're hitting - Where connections are going Most solo devs never look at any of it. Then wonder why things are slow. Paid monitoring tools want $50-500/month to show you this data. But PostgreSQL already has it. Y

Showing the 12 most recent of 20 posts we hold for @postgres. 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.

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

“PostgreSQL Pro | Database Mastery” (@postgres), 1,323 subscribers as measured 29 August 2026. Telegram Register, tgregister.com/channel/postgres.

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.