TfT Performance: Logseq

Open Source, mobile client, extensible, rapid development, that's Logseq. But can it stand up to the demands of my field test and how does it compare to Roam Research?

Jan 07, 2022

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Hej,

And welcome to the Benchmark Results of Logseq, an (mainly) open-source outlining App with support for various operating systems including mobile. Logseq has made huge progress in the past few months and has gathered a large fan base around it.

If you are new here, you may want to read this first:

Gödel's

TfT Performance: Methodology

Introduction If you want to get realistic results from performance tests, you have to create realistic conditions. If you want to compare different applications, you have to use the same data. To ensure this I’ve chosen synthetic test data over a copy of one of my personal knowledge graphs…

4 years ago · 2 likes · Alexander Rink

and

Gödel's

TfT Performance: Machine Room

Hej and welcome to this small interlude, where I talk about the task course, test data, test environment, and some pitfalls with formats and import limits before we dive into the first results. Preface I've been thinking a lot about how to best evaluate the performance of the tools. In everyday use, you rarely come up against limits. And whether an applic…

4 years ago · 1 comment · Alexander Rink

before you dive into this article. Also, the results of Roam Research may be interesting for you, although I will definitely summarize everything again at the end of all the tests.

Gödel's

TfT Performance: Roam Research

Hej, And welcome to the Benchmark Results of Roam Research. If you are new here, you may want to read: and before you dive into this article. Side note I created the following videos essentially for me to measure the times quickly. I've linked them here to prove the results, but they're probably pretty dull despite being partly time-lapse…

4 years ago · 2 likes · 2 comments · Alexander Rink

Side note

I created the following videos essentially for me to measure the times quickly. I've linked them here to prove the results, but they're probably pretty dull despite being partly time-lapse.

All the diagrams I show here use the same color scheme and order—Blue for the 2,000 data set, turquoise for the 5,000, and green for the 10,000. For Logseq, I had to add a 7,500 pages data set in orange because the 10,000 group was too big to handle.

And please remember: We focus here exclusively o…

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