1. X
  2. javier ramirez
Log inSign up
javier ramirez
10.1K posts
Image
user avatar
javier ramirez
@supercoco9
Developer Advocate at QuestDB and all around happy person. Fan of Open Source,Tech Communities,Data&ML.He/him.Ex-AWS,Ex Google Developer Expert. @[email protected]
Madrid, Spain
javier-ramirez.com
Joined March 2007
5,593
Following
5,310
Followers
RepliesRepliesArticlesArticlesMediaMedia

New to X?

Sign up now to get your own personalized timeline!

Create account

By signing up, you agree to the Terms of Service and Privacy Policy, including Cookie Use.

Terms·Privacy·Cookies·Accessibility·Ads Info·© 2026 X Corp.
Don't miss what's happening
People on X are the first to know.
Log inSign up
  • user avatar
    javier ramirez
    @supercoco9
    Jul 8
    I'm speaking at Big Data LDN 2026! I will talk about our experience working with agents to build on top of #QuestDB. If you are in London in September, it is a good opportunity to see what's trending in Data and AI. invt.io/1txb3uyerft #BigDataLDN
    Image
    Connect with me at Big Data LDN!
    From invt.io
    137
  • user avatar
    javier ramirez
    @supercoco9
    May 21
    My kid, who glides through netflix, disney+, amazon prime, and youtube, was totally puzzled today when I asked her to change the TV channel. Same device, same remote. Completely different mental schema
    304
  • user avatar
    javier ramirez
    @supercoco9
    May 13
    These are the type of blog posts I would like to be able to write. My colleague @AndreyPechkurov goes deep to explain how we (ahem, he) added Window Joins to QuestDB, and why it outperforms other database engines.
    user avatar
    QuestDB
    @QuestDb
    May 13
    WINDOW JOIN in #QuestDB is not just syntactic sugar. We published a deep dive into how we parallelized and vectorized it, plus benchmarks against Timescale, DuckDB, and ClickHouse. On the tested workload: 5x faster than the previous QuestDB path. Link in thread 👇
    Dark navy thumbnail with the headline "How we made WINDOW JOIN parallel & vectorized" — WINDOW JOIN in pink, the ampersand in cyan. Below it, a two-stream timeline: a row of bright cyan anchor events on top, and a dense pink data cloud beneath. Eight pink window frames cut vertically from each anchor down through the cloud, with the cloud noticeably denser inside each frame. A small pink pill at the top of every frame labels it T1 through T8, suggesting one thread per window. A line of monospace type along the bottom right reads "8 windows · parallel · SIMD".
    991
  • user avatar
    javier ramirez
    @supercoco9
    Feb 17
    A few weeks ago my colleague @jerrinot noticed an interesting commit in OpenJDK fixing a 7 year old performance issue. He tested it out and found a 400x speed boost. Yesterday the @ThePrimeagen did a rad video featuring his content. Pretty cool! youtube.com/watch?v=R3ydGM…
    771
  • user avatar
    javier ramirez
    @supercoco9
    Jan 9
    How does your database cope with datasets with 6000+ columns? #QuestDB handled them fine, but struggled to copy data across tables. No more. github.com/questdb/questd…. And this is why you *sometimes* need specialised databases
    github.com
    fix(sql): support copies of very wide tables and result sets by nwoolmer · Pull Request #6525 ·...
    Fixes #3312 Fixes #3326 This PR fixes a bug preventing copying of data between tables with thousands (6000+) of columns, through upgrades to RecordToRowCopier. The same bug existed for RecordSink, ...
    274
Advertisement
Advertisement