jovezhong

Another cool option to run local models on macOS. LM Studio might have a better user interface and download experience, but Swama’s pure CLI experience is still awesome!

Blog: https://hackaday.com/2025/04/23/abusing-duckdb-wasm-to-creat... Repo: https://github.com/patricktrainer/duckdb-doom

a great way to abuse DuckDB

I am a bit surprised the recommended/only guide to use this mcp server is via docker run, although running via node should be possible too https://github.com/github/github-mcp-server/issues/111

why only llama3.x models are listed on ollama? llama4 no longer wants to support ollama, to better track the adoption?

"Sadly, ClickHouse is written in C++, not in Rust.".. nice opening

Certainly fun to use. Maybe you will check the docs/demo more seriously, after you type the command in the UI..

The results show Firebolt delivering: 8x better price-performance than Snowflake, 18x better than Redshift, and 90x better than BigQuery. Near-linear concurrency scaling, achieving low latency of 120 milliseconds with a throughput of 2500 QPS

SELECT _flow, _fhigh, _frowts, FORECAST(i32, "algo=lstm,model=lstm_foo,alpha=95,period=10,wncheck=0") FROM foo;

I was wondering how to figure out "when you stare at it for too long", then saw "Uses Mac's built-in front facing camera".. Err, I am not sure whether I want to keep camera on for this..

Typing "thanks" or "great" to AI make me feel better

Claude can help you write a lot of okay Python code. Yes, Go is great, but in this MCP case, because of uvx and pypi, as well as kafka python lib, choosing Python is not bad at all

Nice. I built something similar but with Python https://github.com/jovezhong/mcp-timeplus

with pipy and uvx, it will be a bit easier for others to install the mcp server. Just to add a JSON, without need to download binary manually.

Running a mcp tool is expected to be lightweight. Starting a docker container is not impossible but will make this process a bit heavy. Maybe in the future the MCP client can provide python/nodejs runtime and also have extra flag to allow the users to confirm the requested permissions for certain mcp tools. Today running MCP servers with whatever executable available locally is too risky

most of the MCP tools use Python env (uvx) or Node or even Java to run ANY CODE on your machine, so even the python virtual env is a sandbox but it's to isolate the dependencies not the file/network access. If you are unlucky, you can still install a malware mcp server to clean up your disk or send your photos to somewhere. MCP servers are just local scripts. There are some permission control from deno but this is not the only runtime engine for MCP server. It'll be cool to have something like Chrome extension permission or iOS/Android permission ask, but I highly doubt this will be available since on your local server, there are just too many ways to run scripts.

I use the GitHub Desktop app a lot, every day, the viewing diff there is so clear. But I am happy to use Zed to open multiple projects, switch branch, stage changes, commit and push. Otherwise I have to switch to different repo in the GitHub Desktop. In most cases, I don't need a full IDE, since I only need to make few lines change of a terraform or a markdown file, or update the dependency in a package.json.

Zed is my favorite text editor (IDE?) written in Rust. Sure, VS Code and Cursor are popular, but just like Google Chrome, there are just too many extensions to slow down everything. So I switched from Chrome to Arc, and VS Code to Zed. Very personal choice. But I do miss the Git integration for sure. After trying the private beta of Git integration for a while with Zed preview, so glad to see it's now in the public beta (but still need download the Zed Preview.app)

According to my teammate who actually wrote the C++ code for this, there are lack of documentations of how the AWS_MSK_IAM is supposed to work. He has to check the Java/Python implementation line by line to avoid those guesswork

I tried to find related code with iam and msk in the file names and failed. To get authenticated with MSK, need to get proper signed and pass to the MSK endpoints. Maybe AWS SDK team are just too busy or not get enough customer ask(escalations?) for using C++ to access MSK cluster with IAM only auth.

I don't know exactly why AWS didn't include C++ SDK when they announced all languages are supported. Maybe it's more common today to use Java/Rust/Python to build data products, but C++ is still such a solid case. Anyway, I will try to reach out AWS team to see whether they are open to put this into the AWS SDK for C++

I use 5ire more than ChatGPT app or Claude app, as you can choose different models and install various MCP servers

Hi all, co-founder of Timeplus here. One of our community users tried the 1brc.

At the core, Timeplus is a streaming processor, powered by ClickHouse. So it can leverage thousands of powerful SQL functions from ClickHouse, including `file(file, 'CSV', columns)`.

We are late to the 1brc party, but might be the first as a streaming processor. Powered by ClickHouse, Timeplus can efficiently process both streaming data and historical data, just with SQL.

Feel free to try it yourself and share your number. The author got 39 second. I got 21 seconds. Maybe on M3 Pro, it can be less than 20 seconds. No tuning applied yet.

Love ClickHouse and Kafka? Let Timeplus Proton take it to the next level.

Proton is an open-source streaming processor, written in C++. We’re thrilled to introduce a major upgrade of Proton, which you can now read or write ClickHouse with streaming SQL. You can use Proton as a lightweight streaming processor to get live data from Kafka/Redpanda, apply simple or complex processing logic, then send data to your ClickHouse, no matter in local or in the cloud. You can also JOIN Kafka data with dimensional data in ClickHouse, without moving them to Proton.

I wrote this tutorial to share how to get started using Proton and ClickHouse together. Demo video included. Happy to discuss here.

A deep dive from CTO of Timeplus.

ksqlDB is great for * SQL Interface * Real-Time Streaming Processing * Integration with Kafka * Stateful Processing * Scalability * Security

However, there are also limitations with ksqlDB: * Deep Coupling with Kafka * Heavy Resource Consumption * Not Designed for Analytics * Not True Open-Source

There are lots of similarities between Proton and ksqlDB. Both support: * Stateful streaming processing * Data persistence * Stream/table concept * Dual query mode, long running, unbounded push based query and bounded, pull base query * Query Kafka data and write analytic results back to Kafka

Most features of ksqlDB can be found in Proton, while Proton offers additional benefits: * Proton demonstrates stronger performance * Proton is more flexible when consuming Kafka data * Proton is purpose designed for analytic workloads * Support complex computing by JavaScript UDF (User Defined Function) * Proton is more developer friendly

To explore Proton yourself, visit the [Proton GitHub repo](https://github.com/timeplus-io/proton) or create your own workspace on [Timeplus Cloud](https://timeplus.com).

Today I just tried Zulip, in order to join a dev community. Yes, coming from Slack/Discord background, I felt like Zulip is a bit too much

I mainly use Typora for markdown editing and saving as PDF

Just check pandoc installation and get started guide. Overwhelmingly detailed, like I never use command line before. Maybe it assumes many users of pandoc are writers or Information Developer, without much tech skills.

I've been using Arc since June 2023. I really like it as a product. But the communication is a bit overwhelming. Their CEO and team are fairly good to make noise (in the good way) on YouTube, twitter. But I guess I cannot catch up with their frequent release notes and videos.

Glad to hear that. In the Timeplus Cloud UI, there is a way to visualize the query plan/DAG. Sorry it's not available in command line yet.

SQL is so flexible. When I put myself as a user, I also prefer those tools that provide nice UI for filter/reporting, but also give me SQL interface to do advanced query, such as PostHog, Resmo, JIRA(?)

it's a spicy question.. The full comparison deserves one or a series of blogs

In short, data streaming is getting popular. Apache Flink, Apache Spark, ksqlDB are traditional players. They work well in some cases, but have challenges on easy-to-use, easy-to-deploy, on even performance sometimes

Proton, RisingWave, Materialize, etc are the alternatives. In the end, it's always 'case by case' to pick up the best tools working for your team in your projects.

If you think this is too general, well - Materialize no longer provide the latest code as an open-source software that you can download and try. It turned from a single binary design to cloud-only micro-service - RisingWave has been open-sourced for 1.5 years and released their cloud mid of last year. It builds its own row-based historical storage, while Proton leverages ClickHouse for faster OLAP-like workload. Also there are more SQL functions supported in Proton, because it's powered by ClickHouse. Proton uses local SSD as the main storage and has an option to send older data to object storage. While RisingWave primarily uses object storage, and use local disk as cache. So in general Proton can achieve lower latency for both streaming or historical queries.

I am a big fan of coffee and drink different kinds of coffee over time, even on the same day. It's all about the use cases and preferences. This could be applied to choose open-source tools to query live data. In the last Current conference, me and Gang had a talk about different tools and different coffee. You may check https://www.timeplus.com/post/query-kafka-with-sql-current23

Nice intro, but I am a bit worried not seeing SOC2 or something similar.