PlanetScale
@PlanetScale · joined 04 Feb 2018
The fastest and most reliable database for Postgres & Vitess Discord: https://t.co/vGOpjxYZj9 Support: @planetscalehelp https://t.co/wQJpk2fpGD
43 900Followers
143Following
2 294Posts total
1.5MViews on collected posts
Ultimi post
Cerchiamo nuovi post…
Let's take a closer look at how Neki is built.
Starting with real Postgres, we unpack the architecture one component at a time:
https://t.co/zGdKZp2P7k
8.9K views · 184 likes
· 11 reposts · 5 replies
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We wanted more from full text search in Postgres, so we built TIN. It gives you fuzzy matching, NEAR, wildcards, boolean grouping, and BM25 scoring. Plus, it's really fast.
See it in action in our latest video:
https://t.co/J8bkRGuBM6
11.6K views · 139 likes
· 8 reposts · 4 replies
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@PlanetScale Someone should open source this
215 views · 0 likes
· 0 reposts · 0 replies
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A lot of you asked how to run TIN in CI, so we built Lead: a TIN-compatible search extension, built for local development and CI. Use TIN in prod, Lead in tests.
https://t.co/tsqdMAl3BG
3.7K views · 67 likes
· 9 reposts · 4 replies
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Hop into our Discord for TINTALK: a live Q/A on the industry's fastest Postgres text search.
We'll be joined by Eric and Patrick, PlanetScale engineers and the creators of TIN, to answer all your full-text search questions.
Monday 11am PT. https://t.co/hKnA17V56A
10.7K views · 24 likes
· 2 reposts · 2 replies
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0:28
@PlanetScale Is it weird if I say nice balls?
775 views · 0 likes
· 0 reposts · 0 replies
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@PlanetScale Heading in right direction.. excited to see this.. but looks like the index is on a single column only. For different one columns have to create index. Usually would like to see only a single index like how paradedb does..Can it be used along with joins?
3K views · 2 likes
· 0 reposts · 3 replies
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Today we introduce TIN: a powerful and reliable full-text search extension for Postgres.
TIN works with complicated WHERE clauses, replication, backups, and maintains correct transaction visibility.
It's also mind-blowingly fast. https://t.co/iXgcbcv71m
492.6K views · 2K likes
· 114 reposts · 57 replies
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0:36
Read more about TIN's performance and how to get started:
https://t.co/CcyP2OV4Wx
28.4K views · 159 likes
· 14 reposts · 4 replies
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Neki is now available. https://t.co/XwKtxhWWM8
789.1K views · 1.8K likes
· 132 reposts · 60 replies
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3:27
The magic of a sharded database is not having hundreds of servers. It’s making hundreds of servers behave like one.
https://t.co/0Pi6OeC0CU
4.3K views · 69 likes
· 8 reposts · 0 replies
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@PlanetScale @NickVanWig @BenjDicken @harshitgangal @rohitnayak RSVP’d!
436 views · 1 likes
· 0 reposts · 0 replies
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@PlanetScale @NickVanWig @BenjDicken @harshitgangal @rohitnayak Damn is it recorded or online?
725 views · 2 likes
· 0 reposts · 1 replies
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@PlanetScale @NickVanWig @BenjDicken @harshitgangal @rohitnayak PlanetScale wrote Vitess and spent a decade learning where MySQL sharding actually hurts. Neki is that scar tissue ported to Postgres. A sharding product from the people who already have the scars beats any greenfiel
741 views · 1 likes
· 0 reposts · 1 replies
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We're pulling back the curtain on Neki, our sharded Postgres product, at THE SF DATABASE MEETUP on Sept 10.
The lineup:
@NickVanWig — A first look at Neki's architecture
@BenjDicken — Why Postgres needs sharding
@harshitgangal — The lifecycle of a query in Neki
@rohitnayak —
34.5K views · 104 likes
· 7 reposts · 7 replies
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Unblock stuck connections with live connection management in the PlanetScale CLI and dashboard. Find out more. https://t.co/GoKTBA5E1G https://t.co/THdSSaLd3D
2.6K views · 12 likes
· 2 reposts · 0 replies
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1:13
Every query in Neki gets two plans.
The Neki plan decides which shards run the query and how their results are combined. Postgres then decides how each shard executes its work.
A closer look at the Neki router: https://t.co/gN838rVzDy
8.4K views · 93 likes
· 10 reposts · 0 replies
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Our migration specialists move customers to PlanetScale every day, often at several terabytes per hour. Whatever your workload, we can help.
To get a head start, run our migration assessment tool and share the results with our team:
https://t.co/HNe6y8ZzmX
1K views · 6 likes
· 0 reposts · 1 replies
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After moving to PlanetScale Metal, Autumn saw a 10x decrease in query latency.
"Migration was much easier than we had anticipated. We were worried it’d take us weeks, but it ended up taking only 2 days."
https://t.co/acAhqgyfkw
1.1K views · 6 likes
· 0 reposts · 1 replies
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After repeated outages with their previous provider, OpenSecret migrated to PlanetScale.
Their users never noticed the switch, things just got faster. P99 now sits at 1.0ms, and they're paying 38% less for 4 databases + 8 replicas.
https://t.co/5cVcZzMbwd
840 views · 7 likes
· 0 reposts · 1 replies
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Vitalize moved 400GB and 150M rows to PlanetScale with zero downtime.
"Post migration, life has gotten a lot simpler. Our P95 latency is now just 2ms."
https://t.co/a7babLkcrk
1.7K views · 12 likes
· 0 reposts · 1 replies
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Don't wait until it's critical. We'll help you migrate. https://t.co/3yHwuMm1bw
127.3K views · 330 likes
· 13 reposts · 14 replies
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0:53
Rispetto ad account della stessa dimensione
24 post degli ultimi 90 giorni, accanto alla fascia di 10K–100K follower. arriva a molti, ma pochi di loro reagiscono.
Visualizzazioni mediane2 763questo account924mediana per 10K–100K
Copertura, %6.29%questo account3.62%mediana per 10K–100K
Interazione, %0.57%questo account1.52%mediana per 10K–100K
| Metrica | Questo account | Mediana per 10K–100K | Rapporto |
|---|---|---|---|
| Visualizzazioni mediane per post | 2 763 | 924 | 2.99× |
| Copertura (visualizzazioni ÷ follower) | 6.29% | 3.62% | 1.74× |
| Tasso di interazione | 0.57% | 1.52% | 0.37× |
Altri account di questa fascia → Confronta con un altro account → Come sono costruiti questi parametri →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
7412 Sep
725
436
4.3K3 Sep
789.1K10 Sep
28.4K16 Sep
492.6K
3K
775
10.7K17 Sep
3.7K
215
11.6K18 Sep
8.9K
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.27%2 Sep
0.41%
0.23%
1.78%3 Sep
0.26%10 Sep
0.64%16 Sep
0.44%
0.17%
0.00%
0.31%17 Sep
2.19%
0.00%
1.32%18 Sep
2.25%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes59.8%5 020 in total
Reposts3.9%330 in total
Replies2.0%169 in total
Quotes1.5%127 in total
Bookmarks32.8%2 751 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
Followers by day
8 Sep
Daily snapshots since 08 Sep 2026; the dashed line is the starting count.
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