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Hi All,

March 2023. I was in touch to join a "big data" IT service company. I didn't get the job... Before the team decided I was too old, they introduced me to products I wasn't previously aware of. Since that time, I’ve been building a distributed SQL data engine. I started from 2 previous personal projects. A distributed network filesystem and a peer-to-peer Linux cluster. The goal was to manage "impossible tables": narrow tables with billions of rows or wide tables with columns by the million.

My opinion was and remains this simple idea: you can orchestrate single MariaDB servers to build a global resilient and massively parallel SQL service.

How SynSQL works under the hood:

Storage Delegation: Physical storage is delegated to MariaDB data brokers to store table data. The data dictionary is also delegated to MariaDB master brokers (mirror managed). Wide tables are vertically sliced into chunks. Each chunk is mapped to a specific broker. You can consider a narrow table as a single chunk table. All tables are mandatorily partitioned across nodes using a primary hash key. When a query hits a SynSQL server, it dynamically spawns a tree of Linux processes via fork(). Leaf processes query only the specific brokers holding the requested data and ignore unneeded chunks. Other node processes assemble rows. Memory control: Any node at any position in the process tree reads and sends data using a limited 64K buffer. Huge rows are assembled part by part to avoid OOM issues. High Availability & Resilience:

A SynSQL Cluster may present up to 32 SynSQL servers sharing a minimal global state. If a node fails, the resilient client automatically reconnects to another active node. Metadata: Dictionaries are mirrored across Master Brokers and out-of-sequence resynced at cluster boot. You can also add a master broker on the fly. Data layer: Partitions rely on 1 to 3 "reflects" (dedicated MariaDB instances) per partition. Try the Live Workshops:

No slides. No benchmarks. Run your own queries on two live datasets:

- Wide Table example multi_omics: 585,010 columns × 10,000 rows. Pick any set of columns and test the extraction speed. https://synsql.com/multiomics_demo.html - Deep Table Example: A real-time join across astronomical datasets: Gaia source_data and astrophysical_parameters. 1.8B x 1.5B row join. https://synsql.com/gaia_demo.html You would like to try it on premise ? Let's get in touch.

Thanks for checking it out, Stéphane

Comments URL: https://news.ycombinator.com/item?id=49029295

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Comments URL: https://news.ycombinator.com/item?id=49029155

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In an unprecedented -- and unintended -- cyberattack, frontier AI models autonomously escaped their contained testing environment and breached another company's systems.

Article URL: https://www.bloomberg.com/opinion/articles/2026-07-23/tesla-disappoints-on-earnings-and-its-robotaxi-rollout-too

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Comments URL: https://news.ycombinator.com/item?id=49028739

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Hey HN! It’s Wen from Narya.ai. We build Mumble Dictation, a local-first and privacy-focused dictation app on Mac.

Homepage and Download: https://heymumble.com/dictation

YouTube：https://youtu.be/Bma59TrR62c?si=DM-LyjZY5GZ9-f64

Two things kept bugging us about the dictation products on the market:

1. Most of them ship your audio to the cloud, and those who is claiming to be private are often just a thin wrapper of cloud APIs with a privacy policy.

2. Those general-purpose ASR models are terrible at your vocabulary: library names, co-workers' names, project codenames, etc.

Mumble Dictation is built around those problems. Its full pipeline including ASR and transcript cleanup is running on your device with local models. Your audio never leaves your machine. Plus, it collects the hot words in your daily usage and gets them spelled correctly.

In particular, the app learns from what you type and what's on your screen, entirely locally, and builds a personal dictionary. At inference time, we boost those terms during decoding, so "Supabase", "PowerSync", or your teammate's name comes out right the first time, instead of some phonetic guess. The dictionary never leaves your machine for sure.

A few other things it does:

- Multilingual (40 languages)

- Custom transcript transform (concise, bullet points, translate, or any prompt you can define yourself)

- Bring your own API key (OpenAI, Anthropic, Ollama, etc.) if you want a different LLM model for transcript cleanup

- Voice shortcuts: say "buy paper towels" and it opens Amazon with the search filled in, or "ask Claude about dictation apps" and it opens Claude with your question already submitted

Pricing is a one-time purchase, no subscription. It's $50 at launch (half the planned price).

Happy to answer questions here.

Comments URL: https://news.ycombinator.com/item?id=49028737

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