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Show HN: Omnara – Open-Source Alternative to Claude Managed Agents

Hey y'all, Kartik from Omnara (<a href="https://omnara.com">https://omnara.com</a>) here. We're building an open-source API for running durable agents. You create an agent with an API call, and Omnara runs the agent loop, gives the agent sandboxes to run commands in, and handles secrets, permissions, and RBAC. Each agent's state is stored in Postgres, so agents survive restarts and cost nothing while idle. You can message them and stream their events over the API.<p>You may remember us from our early days, when we made a remote-control phone app for Claude Code and Codex. Since the harness ran on a laptop back then, we had to build a relay to reach it, it stopped when the laptop closed, and moving it to a cloud sandbox meant syncing code and agent state between machines. We didn't think remote-controlling a local agent was end-game for how people would run agents, so we built a new product where the agent runs in the cloud, any client can talk to it through an API, and it can still use your laptop as one of its machines.<p>Anthropic and OpenAI are building hosted versions of this, like Claude Managed Agents and the OpenAI Agents API. Omnara is an open-source version you can run on your own servers and use your own models. It's basically a harness server like the opencode or codex servers, but durable, scalable, with the usual harness features like file and shell tools, subagents, compaction, permission prompts, MCP, skills, memory, yada yada yada.<p>Here's some interesting architectural decisions we made while building this out:<p>Most harnesses, like Claude Code, Codex, OpenCode, Pi, Goose, etc, run the agent loop in one long-lived process that keeps its log in a JSONL or SQLite file. In Omnara, the log is an append-only event log in Postgres, with inputs, model outputs and tool calls stored as typed rows in their own tables. The loop runs on stateless workers in the control plane. A worker runs one iteration of the loop, either a model call or the tool calls it produced, then releases the agent and puts the next iteration on a queue in Postgres. Whichever worker is free picks it up, so each iteration of an agent's loop can run in a different process on a different machine. Each iteration's result commits in one transaction, so the model output, its tool calls, usage and the next wakeup are saved together or not at all. If a worker dies mid-iteration, nothing commits, its lease expires, and another worker retries it. Agents waiting on a user, a tool or a retry don't hold a worker, so one worker can multiplex thousands of agents.<p>Also unlike other harnesses, the machines that the workers (our agent loop) run on aren't where the agent runs its commands. Instead, any macOS or Linux machine with an internet connection, like your laptop or any cloud sandbox, can run a small daemon (omnarad) that connects out to Omnara, so it doesn't need any open inbound ports. The agent then gets tools for that machine, like running a command or editing a file. An agent can have any number of machines connected to it. A fun thing I like to do is I have my laptop and a cloud sandbox connected to the same agent, so when my laptop is on, my agent codes there and I can interact with it, and I have it often push to Github. When I close my laptop, my agent sees the laptop went offline, pulls the latest changes to its cloud sandbox, and continues there.<p>The entire codebase is open source at <a href="https://github.com/omnara-ai/omnara" rel="nofollow">https://github.com/omnara-ai/omnara</a>, and it’s self hostable, even on a single machine with docker compose. You can also use the hosted version at <a href="https://omnara.com">https://omnara.com</a>. Let me know what you think!

Show HN: Rouler – Steer Windows traffic per app or IP across multiple interfaces

Hi HN,<p>Rouler is "rules for your routes". It allows you to steer network traffic across multiple network interfaces on Windows. For example:<p>- Run Tailscale, Mullvad and OpenVPN official clients simultaneously.<p>- Use Rouler to send Slack via the OpenVPN connection, Chrome + an IP range via Tailscale and a torrent client via Mullvad.<p>Rouler is VPN agnostic, so you can "split-tunnel" with anything that sets up a windows network interface.<p>I'm an independent developer from Australia and have been working on Rouler for a bit over a year. It's been a challenging project to say the least, but I'm really happy with how it's turning out. I have spent a great deal of time building and throwing things away, starting over, belting the initial poc into something that I find intuitive... hopefully others do too!<p>I've done all the testing, fixing and improving I can, so now it's open for public beta. I'd love to hear your feedback... and there are some specific points I'm interested in hearing about listed on the Rouler website. Please reply with any questions you might have.<p>Thanks for reading!<p>Brendan<p>p.s. Rouler is "built in Rust" TM ;-)<p>---<p>On AI (skip if you're sick of hearing about it):<p>Since AI is the hot topic and people are naturally cautious about it, I'll add some quick notes about it, specifically about the driver development as that's the key thing to get right. The driver is hand written and every detail has been poured over many times over. I spent somewhere around 6-9 months manually building and testing just the driver, staring at Dbgview logs, wireshark logs, windows route tables, restarting VM's back to their snapshot and manually copying things across to start again. That's not always the most efficient way of doing things, but it's the way it had to be done. If I had tried to vibe code it Rouler simply wouldn't exist. I did try to lean on AI at times, but it constantly sent me in the wrong direction, told me things weren't possible, tried to take shortcuts and implement poor performing trade-offs. It also loved to hallucinate the windows api. Keep in mind this was around the Opus 4.1 - 4.6 days.<p>Outside of the driver, in user mode land, AI has crept more and more into my workflow. I've had a lot of success utilising the latest models in the app in particular, and I purposefully separated the UI and core logic so I'm able to quickly iterate on the UI. I've also found AI very useful for scripting and refactoring. It has built some great scripts that would've taken me days or weeks to build and fine tune.

Show HN: Clerkenwell – A Handwritten Clojure Notebook

Show HN: Sumi.css – CSS Framework

Show HN: I told people I'm a convicted felon after 20 years of hiding it

Hi there.<p>I was engineer number 3 at Eventbrite and founding engineer at Reforge. I've created a dozen or so startups myself and have worked in many others, like Instacart. All this time, no one knew that I was a convicted felon.<p>It wasn't exactly a topic that came up, but it was certainly something that I never brought up. When you're a convicted felon, people look at you as if you are tainted.<p>I was unable to rent apartments in San Francisco. I was unable to get a job directly after being released from prison. It's funny because when you owe the state $17,000 in restitution and you can't get a job, people become extremely desperate. And that desperation can easily put you right back into prison.<p>So I went from homeless person at age 19 to 7-figures about 10 years later. I retired at age 38.<p>What I'm doing now is writing an autobiography. The main theme of it is hope.<p>And I want to make sure that people know about it. They don't necessarily have to be interested in it, but if people know about what it's like sleeping in a car believing that one day you will travel the world and then actually doing it, then I think I've accomplished my task in writing this book.<p>If you're interested, please let me know.

Show HN: RoadRash ported to Three.js to run in the browser

Road Rash was one of my favourite PC games growing up. I wanted to play it again, but the browser emulators I tried felt sluggish, so I decided to build a browser version using Three.js.<p>This started mostly out of nostalgia. I wanted to be able to open a link and get back to racing and knocking people off their bikes.

Show HN: Penmentor – Claude marks up your handwritten math like a teacher

Show HN: Penmentor – Claude marks up your handwritten math like a teacher

Show HN: Jev Cards, Can you beat a vision model at a picture quiz?

I built a quiz game around TypeSafe's new Jev model, which has vision capabilities. Jev looks at a picture and a question and picks an answer (or taps a place) in about a quarter of a second.<p>I've always loved quiz games and thought this would be a fun way to see what it can do and how fast it is. I made the cards from scratch, and Jev gets exactly the picture you see. More cards will come over time.<p>Play against Jev on your own (there's a leaderboard for each mode), or start a live match and challenge your friends, with Jev as one more player.<p>The code is open source, so feel free to build your own game or make more cards that I can publish.<p>Play: <a href="https://jevcards.com" rel="nofollow">https://jevcards.com</a> Code: <a href="https://github.com/Jose-Sabater/jevcards" rel="nofollow">https://github.com/Jose-Sabater/jevcards</a> (the newest cards stay private for a while)<p>Disclaimer: I ran Jev through both TypeSafe and Opper, and made the cards through Opper's vision models and Claude Code. I work at Opper, but jevcards is open source and free to play.

Show HN: Jev Cards, Can you beat a vision model at a picture quiz?

I built a quiz game around TypeSafe's new Jev model, which has vision capabilities. Jev looks at a picture and a question and picks an answer (or taps a place) in about a quarter of a second.<p>I've always loved quiz games and thought this would be a fun way to see what it can do and how fast it is. I made the cards from scratch, and Jev gets exactly the picture you see. More cards will come over time.<p>Play against Jev on your own (there's a leaderboard for each mode), or start a live match and challenge your friends, with Jev as one more player.<p>The code is open source, so feel free to build your own game or make more cards that I can publish.<p>Play: <a href="https://jevcards.com" rel="nofollow">https://jevcards.com</a> Code: <a href="https://github.com/Jose-Sabater/jevcards" rel="nofollow">https://github.com/Jose-Sabater/jevcards</a> (the newest cards stay private for a while)<p>Disclaimer: I ran Jev through both TypeSafe and Opper, and made the cards through Opper's vision models and Claude Code. I work at Opper, but jevcards is open source and free to play.

Show HN: VoidAccess – open-source dark web OSINT, from query to a graph

Hi HN! Im Katriel, and im a Security Researcher/Enthusiast and in the wave of AI, i wanted to build that next gen of security tooling that surpasses the current tools, and even the paid industries with an open source engine. I built MailAccess as well, which is going to be the best damn email osint tool out there, in another year. But just before building MailAccess i built VoidAccess, because i was delving a lot into DarkINT and the content inside the dark web is too difficult to navigate through for a human, so i automated that pipeline, made sure the noise was removed, and anything NSFW was filtered out, to give the analyst an overview of what is present in the dark web, without having to actually go through it manually.<p>Very simple to run, you just run a few commands to install, and a couple to investigate. Then the engine takes over, and stops onyl when the job is done(or at a particular time limit, if set by the user).<p>Do check it out, if that is something that interests you.<p>Thanks to the community for giving it the love it has got till now.

Show HN: VoidAccess – open-source dark web OSINT, from query to a graph

Hi HN! Im Katriel, and im a Security Researcher/Enthusiast and in the wave of AI, i wanted to build that next gen of security tooling that surpasses the current tools, and even the paid industries with an open source engine. I built MailAccess as well, which is going to be the best damn email osint tool out there, in another year. But just before building MailAccess i built VoidAccess, because i was delving a lot into DarkINT and the content inside the dark web is too difficult to navigate through for a human, so i automated that pipeline, made sure the noise was removed, and anything NSFW was filtered out, to give the analyst an overview of what is present in the dark web, without having to actually go through it manually.<p>Very simple to run, you just run a few commands to install, and a couple to investigate. Then the engine takes over, and stops onyl when the job is done(or at a particular time limit, if set by the user).<p>Do check it out, if that is something that interests you.<p>Thanks to the community for giving it the love it has got till now.

Show HN: Death Plan Switch, a self-hosted dead man's switch for solo devs

Hi HN,<p>I'm Peter Bishop and I've been working in graphics and web tech for over 25yrs.<p>I've recently launched Death Plan Switch to solve a major problem in my succession plan. What if I go missing or die? The right people are told and my business can continue to operate for my clients.<p>There's a backstory to this project, I was hospitalised in 2012 and lost my business back then and I couldn't get the data to my technical 2IC in time without frustrating my clients.<p>Death Plan Switch solves this problem, it's free to download and use or study under the MIT license.<p>I've been using it for the last few weeks. It was authored with the help of Claude Code after writing an extensive MD document and it passed 42 unit tests.<p>I hope you get some use out of it, or it inspires your own succession plans. My clients are telling me this is a strong sales feature when they trust me with their hosting and technology accounts.<p>Happy to answer any questions.<p>Kind regards, Peter Bishop.

Show HN: Death Plan Switch, a self-hosted dead man's switch for solo devs

Hi HN,<p>I'm Peter Bishop and I've been working in graphics and web tech for over 25yrs.<p>I've recently launched Death Plan Switch to solve a major problem in my succession plan. What if I go missing or die? The right people are told and my business can continue to operate for my clients.<p>There's a backstory to this project, I was hospitalised in 2012 and lost my business back then and I couldn't get the data to my technical 2IC in time without frustrating my clients.<p>Death Plan Switch solves this problem, it's free to download and use or study under the MIT license.<p>I've been using it for the last few weeks. It was authored with the help of Claude Code after writing an extensive MD document and it passed 42 unit tests.<p>I hope you get some use out of it, or it inspires your own succession plans. My clients are telling me this is a strong sales feature when they trust me with their hosting and technology accounts.<p>Happy to answer any questions.<p>Kind regards, Peter Bishop.

SimCity, but with Permits

Show HN: Ranet3 – High performance policy routed IPsec mesh SD-WAN

btw this is already running on all my machines (including a macbook), and i've configured all of them to have routable public ip addresses ;)<p>especially for the mac, my ISP is SFR (over coaxial connection) with only dynamic ipv4, i can use this to get stable v4/v6 addresses very easily for all my devices behind the router<p>ios/android app soon^{TM}

Show HN: I built a task system to handle the drudgery so I could focus on tasks

I'm a software engineer from the east coast (who has lived in Boston, NY, the bay area, UK, France), and I built a task system called 3 & Done. It's the place you trust to store everything you need to do. It accepts voice input for rapid entry, as well as text (it stores the audio locally so you can listen to jog your memory) and emails you every morning with the three most important things for you to do that day, and why, based on what you've said about the task: deadlines, urgency, sitting too long.<p>I've been at software engineering for about 44 years now... Grew up with it, which was unusual when I started, and I was always good about getting into the zone and doing things. The career started small, small company, then back office, the dot com startups, then smaller companies again after the bust, a non-profit, and eventually YouTube (Google at the time, but just barely) and Meta (just Facebook when I was there).<p>When I hit the startups, and later big tech, it was no longer enough to just be an engineer, to have drive, to be good, you had to be organized, you had to follow through, get stuff done, and that's where the task systems started. Twenty-five over the years (and yes, I've actually counted), from Moleskine notebooks with Getting Things Done, evernote (remember evernote?), bug trackers, todoist, asana, google keep, among others.<p>When I managed on the Facebook News Feed, I got into gantt charts (for me and my team), spreadsheets, OmniPlan... I remember apologizing to my director for being so disorganized (because I felt I was making a mess of it), and he told me that I was the most organized engineer he knew.<p>That was because I was doing all of the work in the background, the trimming, the sorting, the reviews, but it was just so much work. Which was why I changed from system to system. Each time it built up, and I had to spend more time looking at things I couldn't or didn't get done, when I was rushed and couldn't put time into today's review, it would pile up, and then using it was so much work that I would start taking mini-notes, just emailing myself a few things to do the next day.<p>That's actually the thesis of the app (but not where it started), that if I could just have a few things to do emailed to me each day, I could get it done.<p>This app actually started when I described my previous startup failures into a Claude web session, and it repeated back to me what I had just said. My previous failures were because I spent too much time building the stuff I needed, and not building what I was supposed to be building.<p>I decided that the app would email me three things to do every day (which matches best practices for attention), but that the day was always yours to decide. We won't overload you, but you can add more, if you're feeling up to it, or cut back, and we never shame and try our best not to nag (I often only finish two). If we get it wrong, you can tell us, and we'll re-rank it once a day, or you can set it manually, and if you do, we never override that choice. The web app is live, and native for both platforms is coming. In the meantime, on Android, you can use gestures to quick launch into the voice input so saving a task is only a gesture away (e.g. double-tap the back of a Pixel, double-press the power button on Motorola).<p>Now let's talk about the dirty parts. I used AI to help me build this. Anthropic models mostly, and the brains of the app come from Anthropic models (I like the quality, I like the privacy, absolutely no training on customer data, and the stance of the company). This app is not some one-shot wonder where I asked frontier models to build a task system and then I put it on a server to show you.<p>I have prompts for the various features (e.g. ranking, generating suggestions, task extractions), I have eval sets of task lists (not anyone's real tasks, but constructed from patterns in my tasks, or the tasks of testers who allowed me to fix the problems they were having), with the three I expect to come out. I store the eval outputs, and re-test whenever I add a new rule to a prompt, or whenever testing a new model version. The great thing about having this eval set is that it catches when I get it wrong. When I introspect a failed run, sometimes it's because I need to tune a prompt, but sometimes it's because I missed something in my own ranking.<p>I did the same thing with my infrastructure as well, so this time, instead of setting up servers, and building login systems, and managing databases, I built on Vercel (git push to serving Next.js), Neon (hosted postgres).<p>I started getting emails mailed to me by mid-June, but started getting usable suggestions on June 26, and I've been using it every morning since. I wanted it to be easy to get started, and easy to use, so the input handles mess (you can add multiple tasks in the same run-on sentence, and a friend who helped me test it just pasted his entire obsidian todo list in wholesale to get started).<p>I wanted to make sure that anyone could try it out, so I built a trial feature that uses the real in-app ranking with a list of items you provide.<p>If you want to try the service, there's a free 14-day trial (card required), and then it's $99/year or $9.99/month after that (plus sales tax). We warn you seven days before your card is charged and if you cancel, you keep access through the term (either the trial, or our last paid period). Online, through settings -> billing, no email, no call.<p>I really hope you'll try it out. If you do, please tell me if we did a good job picking out your day.<p><a href="https://3anddoneapp.com/try" rel="nofollow">https://3anddoneapp.com/try</a>

Show HN: I built a task system to handle the drudgery so I could focus on tasks

I'm a software engineer from the east coast (who has lived in Boston, NY, the bay area, UK, France), and I built a task system called 3 & Done. It's the place you trust to store everything you need to do. It accepts voice input for rapid entry, as well as text (it stores the audio locally so you can listen to jog your memory) and emails you every morning with the three most important things for you to do that day, and why, based on what you've said about the task: deadlines, urgency, sitting too long.<p>I've been at software engineering for about 44 years now... Grew up with it, which was unusual when I started, and I was always good about getting into the zone and doing things. The career started small, small company, then back office, the dot com startups, then smaller companies again after the bust, a non-profit, and eventually YouTube (Google at the time, but just barely) and Meta (just Facebook when I was there).<p>When I hit the startups, and later big tech, it was no longer enough to just be an engineer, to have drive, to be good, you had to be organized, you had to follow through, get stuff done, and that's where the task systems started. Twenty-five over the years (and yes, I've actually counted), from Moleskine notebooks with Getting Things Done, evernote (remember evernote?), bug trackers, todoist, asana, google keep, among others.<p>When I managed on the Facebook News Feed, I got into gantt charts (for me and my team), spreadsheets, OmniPlan... I remember apologizing to my director for being so disorganized (because I felt I was making a mess of it), and he told me that I was the most organized engineer he knew.<p>That was because I was doing all of the work in the background, the trimming, the sorting, the reviews, but it was just so much work. Which was why I changed from system to system. Each time it built up, and I had to spend more time looking at things I couldn't or didn't get done, when I was rushed and couldn't put time into today's review, it would pile up, and then using it was so much work that I would start taking mini-notes, just emailing myself a few things to do the next day.<p>That's actually the thesis of the app (but not where it started), that if I could just have a few things to do emailed to me each day, I could get it done.<p>This app actually started when I described my previous startup failures into a Claude web session, and it repeated back to me what I had just said. My previous failures were because I spent too much time building the stuff I needed, and not building what I was supposed to be building.<p>I decided that the app would email me three things to do every day (which matches best practices for attention), but that the day was always yours to decide. We won't overload you, but you can add more, if you're feeling up to it, or cut back, and we never shame and try our best not to nag (I often only finish two). If we get it wrong, you can tell us, and we'll re-rank it once a day, or you can set it manually, and if you do, we never override that choice. The web app is live, and native for both platforms is coming. In the meantime, on Android, you can use gestures to quick launch into the voice input so saving a task is only a gesture away (e.g. double-tap the back of a Pixel, double-press the power button on Motorola).<p>Now let's talk about the dirty parts. I used AI to help me build this. Anthropic models mostly, and the brains of the app come from Anthropic models (I like the quality, I like the privacy, absolutely no training on customer data, and the stance of the company). This app is not some one-shot wonder where I asked frontier models to build a task system and then I put it on a server to show you.<p>I have prompts for the various features (e.g. ranking, generating suggestions, task extractions), I have eval sets of task lists (not anyone's real tasks, but constructed from patterns in my tasks, or the tasks of testers who allowed me to fix the problems they were having), with the three I expect to come out. I store the eval outputs, and re-test whenever I add a new rule to a prompt, or whenever testing a new model version. The great thing about having this eval set is that it catches when I get it wrong. When I introspect a failed run, sometimes it's because I need to tune a prompt, but sometimes it's because I missed something in my own ranking.<p>I did the same thing with my infrastructure as well, so this time, instead of setting up servers, and building login systems, and managing databases, I built on Vercel (git push to serving Next.js), Neon (hosted postgres).<p>I started getting emails mailed to me by mid-June, but started getting usable suggestions on June 26, and I've been using it every morning since. I wanted it to be easy to get started, and easy to use, so the input handles mess (you can add multiple tasks in the same run-on sentence, and a friend who helped me test it just pasted his entire obsidian todo list in wholesale to get started).<p>I wanted to make sure that anyone could try it out, so I built a trial feature that uses the real in-app ranking with a list of items you provide.<p>If you want to try the service, there's a free 14-day trial (card required), and then it's $99/year or $9.99/month after that (plus sales tax). We warn you seven days before your card is charged and if you cancel, you keep access through the term (either the trial, or our last paid period). Online, through settings -> billing, no email, no call.<p>I really hope you'll try it out. If you do, please tell me if we did a good job picking out your day.<p><a href="https://3anddoneapp.com/try" rel="nofollow">https://3anddoneapp.com/try</a>

Show HN: KiviDB, a faster Redis-compatible memory database and vector cache

Hi all,<p>So I have been working on this project KiviDB from February 2026. It started as a project for me to understand rust, having a product with no GC pauses, memory blow up after snapshots and getting OOM on running pods, and that was actually an issue I faced with Dragonfly. I wanted to have something picking the best of Rust, but also picking the best parts of other alternatives like Garnet and Dragonfly. I used AI a lot, but I was the one making the design decisions based on the tests that claude picked from my history of troubleshooting sessions as part of my job. KiviDB supports both RESP2 and RESP3 protocol. I had some founders credits on my AWS account which helped me with the infra, and running instances I could perform benchmark on.<p>Its keyspace is sharded across threads, it is multi-threaded in nature, and performs best on Linux due to io_uring, I used the tokio_uring crate for this. It also has tokio fallback for other OS's. I hadn't open sourced it until recently as I felt it was not ready yet, the best way to learn it was to build a cloud managed service for it across all three widely used cloud providers i.e AWS, GCP and azure. Since I used to mainly work with cloud, I had some insights on what would be the best ways for the deployments, how to conduct failovers, manage SLAs, etc. And that's what I took help from claude to fast pace it. The website does look like AI slop but it works for now, given my limited resources, that's all I had. You may check it out at : <a href="https://kividb.io" rel="nofollow">https://kividb.io</a>, I open sourced the core engine under AGPLv3, didn't want to have just source available, because that is available with other tools too. It supports apprx 98-99% of the redis 8.10 commands, few have issues and you can find them at <a href="https://github.com/kividbio/kividb/issues" rel="nofollow">https://github.com/kividbio/kividb/issues</a>, contributors are welcome.<p>Now the numbers, for the final benchmark, I used 2 c7gn.metal servers, in the same placement group in us-east1, and I used memtier-benchmark tool for this. The setting was : 10M keys, 100B each, 32 cores in use with both pipeline and un-pipelined runs.<p>pipeline 16 GET: KiviDB 21.2M ops/sec vs Dragonfly 2.0 9.1M, Redis 8.10 2.4M, Redis Cluster 32 shards 4.7M<p>When not pipelined, Dragonfly performed slightly better at 3.35M ops/sec vs kividb at 3.07M ops/sec. Memory per key was also slightly worse than dragonfly and almost same as Redis, 177B (kividb) vs 134B (dragonfly) vs 178B (redis).<p>With vector ingestion times it was slower but when querying, it was faster than most alternatives at lower ef, however slower than dragonfly at high ef. Most of the technical details are mentioned here so you can check it out: <a href="https://kividb.io/benchmarks" rel="nofollow">https://kividb.io/benchmarks</a>.<p>easiest way to try it: docker run -d -p 6380:6380 kividb/kividb<p>I am looking forward to building a community around this, provide better rust based tools, I am open to constructive criticism and value informed opinion. Thanks

Show HN: KiviDB, a faster Redis-compatible memory database and vector cache

Hi all,<p>So I have been working on this project KiviDB from February 2026. It started as a project for me to understand rust, having a product with no GC pauses, memory blow up after snapshots and getting OOM on running pods, and that was actually an issue I faced with Dragonfly. I wanted to have something picking the best of Rust, but also picking the best parts of other alternatives like Garnet and Dragonfly. I used AI a lot, but I was the one making the design decisions based on the tests that claude picked from my history of troubleshooting sessions as part of my job. KiviDB supports both RESP2 and RESP3 protocol. I had some founders credits on my AWS account which helped me with the infra, and running instances I could perform benchmark on.<p>Its keyspace is sharded across threads, it is multi-threaded in nature, and performs best on Linux due to io_uring, I used the tokio_uring crate for this. It also has tokio fallback for other OS's. I hadn't open sourced it until recently as I felt it was not ready yet, the best way to learn it was to build a cloud managed service for it across all three widely used cloud providers i.e AWS, GCP and azure. Since I used to mainly work with cloud, I had some insights on what would be the best ways for the deployments, how to conduct failovers, manage SLAs, etc. And that's what I took help from claude to fast pace it. The website does look like AI slop but it works for now, given my limited resources, that's all I had. You may check it out at : <a href="https://kividb.io" rel="nofollow">https://kividb.io</a>, I open sourced the core engine under AGPLv3, didn't want to have just source available, because that is available with other tools too. It supports apprx 98-99% of the redis 8.10 commands, few have issues and you can find them at <a href="https://github.com/kividbio/kividb/issues" rel="nofollow">https://github.com/kividbio/kividb/issues</a>, contributors are welcome.<p>Now the numbers, for the final benchmark, I used 2 c7gn.metal servers, in the same placement group in us-east1, and I used memtier-benchmark tool for this. The setting was : 10M keys, 100B each, 32 cores in use with both pipeline and un-pipelined runs.<p>pipeline 16 GET: KiviDB 21.2M ops/sec vs Dragonfly 2.0 9.1M, Redis 8.10 2.4M, Redis Cluster 32 shards 4.7M<p>When not pipelined, Dragonfly performed slightly better at 3.35M ops/sec vs kividb at 3.07M ops/sec. Memory per key was also slightly worse than dragonfly and almost same as Redis, 177B (kividb) vs 134B (dragonfly) vs 178B (redis).<p>With vector ingestion times it was slower but when querying, it was faster than most alternatives at lower ef, however slower than dragonfly at high ef. Most of the technical details are mentioned here so you can check it out: <a href="https://kividb.io/benchmarks" rel="nofollow">https://kividb.io/benchmarks</a>.<p>easiest way to try it: docker run -d -p 6380:6380 kividb/kividb<p>I am looking forward to building a community around this, provide better rust based tools, I am open to constructive criticism and value informed opinion. Thanks