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OpenHFT
Chronicle-Queue
Java2014–2025
OpenHFT / Chronicle-Queue

Chronicle-Queue

Micro second messaging that stores everything to disk

6Distinct people
6Mentions
0Explicit recommenders
3.8KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Micro second messaging that stores everything to disk

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year6 dated mentions

Observed mentions: 2014-09-11 19:26:20 UTC to 2025-08-06 20:29:11 UTC.

0122014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC101
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC000
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC211
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

6 sources
I spent almost 6 years trading crypto. Our best month's volume was $6B. 1. Nothing we tried with usual strategies worked consistently. Backtesting parameters, ML with smart feature selection, boosting, neural networks - everything failed out of sample. Maybe we were dumb, I don't know. 2. What worked was having a clear edge: - Private exchange programs with rebates for high-volume teams - Pure latency arbitrage - Weird arbitrage trading obscure instruments (e.g. on chain AMMs vs crypto exchange futures). Both market maker and arbitrage strategies were very sensitive to latency. We built a low-latency trading engine in Java (on top of https://github.com/OpenHFT/Chronicle-Queue). We got 130mqs from market event to order send in a hot loop on 99.99 percentile. It was fun to optimize and benchmark. - Tail latency matters. You can hav
Read the rest
e 100ms at the 90th percentile and 10-50ms at the 99.9th percentile. For low latency strategies, this is pure loss. - Tail latency matters even more when markets go crazy. Event rates can jump from 10 per second to 1-2k per second. If your trading engine uses trades or bid/ask events, be ready. For OHLC bars it doesn't matter, but nothing based on OHLC worked for us. --- p.s. I wouldn't recommend trading to anyone. It's very stressful and exhausting. More importantly, all your hard work disappears like trying to hold sand in your hands. There's very little compounding of your work. Strategies constantly churn. You're always negotiating with managers for fees and API limits. You're always negotiating with managers for fees and API limits. They force you to buy and hold exchange tokens like Binance's BNB just to get slightly better fees, VIP status, or direct API access that bypasses firewalls. The industry is extremely secretive - it's a zero-sum game with no incentive to share anything. When you meet someone who trades, it's usually hard to have a meaningful conversation. At least that was true for me. All our strategies were small-scale and we couldn't invest all our capital in them. So discussing what we did was basically saying "yes, we print money, here's how you can take it from us". Overall, I was super lucky. We built a money-printing machine that worked for a few years. But in the end, my co-founder and I decided not to pursue it long-term. One day when yet another strategy stopped working, we just shut down all operations.
In NautilusTrader: Open-source algorithmic trading platform
Nothing taught me as much about API design and testing as Google's Guava. I know there are lots of minor gripes with that library, but is it so incredibly consistent. It is also amazing that no one mentioned the Java Collections (ArrayList, LinkedList, HashSet, HashMap, TreeSet, TreeMap). They are some of the highest quality generic collections that exist anywhere. (For C++, I would say the same about an STL implementation by a high quality project like VCC/GCC/Clang.) For "Java high honors", try to understand how concurrent collections work, e.g., ConcurrentHashMap! For highly specialised containers, try: (1) https://labs.carrotsearch.com/hppc.html, (2) https://github.com/OpenHFT/Chronicle-Queue, and (3) https://github.com/LMAX-Exchange/disruptor
In Why I Like Java (2014)

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