Pekka Enberg ✓

@penberg · Espoo, Finland 🇫🇮🇪🇺 · joined 03 Jan 2010

Founder & CTO @tursodatabase; previously @ScyllaDB and Linux kernel. Author of "Latency" (https://t.co/XWRFq71WaJ).

20 159Followers

1 235Following

10 990Posts total

66.7KViews on collected posts

โพสต์ล่าสุด

Pekka Enberg ✓@penberg5 Sep

What are the best books on formal verification I should read? Asking for a friend… 15.6K views · 151 likes · 10 reposts · 11 replies Open on X →

Pekka Enberg ✓@penberg4 Sep

@penberg @TigerBeetleDB Terrible protocol that shamelessly copied raft 1.5K views · 8 likes · 0 reposts · 3 replies Open on X →

Pekka Enberg ✓@penberg4 Sep

@penberg Also having fun the same way, but for me it’s paxos 🙃 https://t.co/UkCpggaLZv 314 views · 8 likes · 0 reposts · 0 replies Open on X →

Pekka Enberg ✓@penberg4 Sep

@penberg You might find Veil useful! https://t.co/WVy4KlwGED 841 views · 5 likes · 0 reposts · 2 replies Open on X →

Pekka Enberg ✓@penberg4 Sep

Went back and finished my Viewstamped Replication implementation in Rust. Protocol only, I/O is provided by the caller. Verified with a TigerBeetle-style simulator. Now thinking about doing some verification with Lean... https://t.co/uOF8muZNTa 29.6K views · 251 likes · 32 reposts · 13 replies Open on X →

Pekka Enberg ✓@penberg1 Sep

I love @mitchellh's approach to performance engineering. Make it fast on the low end, and you have something amazing on the high end. 7.5K views · 130 likes · 5 reposts · 5 replies Open on X →

Pekka Enberg ✓@penberg31 Aug

This arrived today! Hopefully I will learn how to make my language model training faster https://t.co/fypFX7YFPb 4K views · 78 likes · 4 reposts · 4 replies Open on X →

Pekka Enberg ✓@penberg29 Aug

You think you know something about latency and databases... But then you spend half a day digging into bad transaction tail-latency, only to rediscover what you should already know: consumer-grade NVMe drives are pretty terrible if you push them hard enough. 🙈 7.4K views · 118 likes · 1 reposts · 7 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

8 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 10K–100K ผู้ติดตาม แสดงต่อคนมากกว่าบัญชีขนาดเดียวกัน.

ยอดดูมัธยฐาน5 688บัญชีนี้924ค่ามัธยฐานของ 10K–100K

การเข้าถึง, %28.21%บัญชีนี้3.62%ค่ามัธยฐานของ 10K–100K

การมีส่วนร่วม, %1.41%บัญชีนี้1.52%ค่ามัธยฐานของ 10K–100K

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ 10K–100K	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	5 688	924	6.16×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	28.21%	3.62%	7.79×
อัตราการมีส่วนร่วม	1.41%	1.52%	0.93×

บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

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

7.4K29 Aug

4K31 Aug

7.5K1 Sep

29.6K4 Sep

841

314

1.5K

15.6K5 Sep

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.71%29 Aug

2.14%31 Aug

1.87%1 Sep

1.01%4 Sep

0.83%

2.55%

0.74%

1.11%5 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes60.1%749 in total

Reposts4.2%52 in total

Replies3.6%45 in total

Quotes0.2%3 in total

Bookmarks31.9%397 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

โพสต์ล่าสุด

เทียบกับบัญชีขนาดเดียวกัน

Growth & engagement

Views per post

Engagement rate per post

What the audience does

บัญชีที่คล้ายกัน