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tidwall
redcon
Go2016–2024
tidwall / redcon

redcon

Redis compatible server framework for Go

2Distinct people
3Mentions
0Explicit recommenders
2.3KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Redis compatible server framework for Go

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, 3:56:07 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 year3 dated mentions

Observed mentions: 2016-08-20 18:39:28 UTC to 2024-03-17 17:52:14 UTC.

0122016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments20162017-01-01 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): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20202021-01-01 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): 0 mentions; 0 submissions, 0 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; 1 submissions, 0 comments2024

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
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC211
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 UTC000
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 UTC000
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 UTC110

What Hacker News says

3 sources
ihucos·Mar 17, 2024Submission

Should I write my own Redis?

Hello, there is an excellent library for golang which allows you to implement the redis server protocol: https://github.com/tidwall/redcon I would like to put in the effort to implement most redis commands there and map them to SQL, so that all data can be saved inside a fine tuned sqlite. Essentially if this is implemented we would have a database compatible to redis, the difference is that data is saved to disk and not to RAM. Is there a use case for that? Do people want that? There is some interesting things that could be done with that but I am not sure if the world needs this.
1 points · Open discussion
> how many simultaneous concurrent (client) connections does this support? The client connections are very lightweight. The protocol library is based on https://github.com/tidwall/redcon. I don't have exact numbers but this link may be helpful (which compares Redcon to Redis): https://simongui.github.io/2016/10/24/benchmarking-go-redis-.... I've seen it handle 16K+ client connection without issue, but typically a client library that supports pooling should be used (like Redigo). > how many simultaneous moving objects and at what update frequency? Depends on the complexity of the objects, the number of nearby objects, and the server hardware. Each collection of objects consists of one btree and one rtree for key/id lookups and spatial queries respectively. So updating a single point is like O(log(n)+log(m)). An in-memory database like Tile
Read the rest
38 can achieve 100K+ per second. Utilizing network pipelining can help out too. FYI, I use a 4-core server with 8GB ram for testing. In the case of a roaming geofence (http://tile38.com/topics/roaming-geofences), following each update there an additional query of the rtree O(log(n)) to retrieve nearby neighbors. If there's a lot of nearby objects, this can result in a lot of data sent over the network. But in general, a collection of millions of points spread over a continent with 100K+ updates per second should work, while keeping with realtimelyness. > Do these limits change if the shapes get complicated? Yes. Complicated objects such are MultiPolygons may require additional calculations like raycasting.
In Tile38 – Realtime geofencing and geospatial index, v1.7.0

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