Saturday, July 18, 2026

pgrust: PostgreSQL => Rust, with AI: 300x speedup

Postgres was rewritten in Rust… and somehow passed every test - YouTube

Based on the video from Better Stack, here is a quick summary of pgrust:

  • What it is: An experimental rewrite of PostgreSQL in Rust.

  • Compatibility: It successfully passes all 46,066 official PostgreSQL regression queries, works with standard psql clients, and can boot directly from an existing Postgres 18.3 data directory.

  • Architecture Shift: It replaces Postgres' traditional process-per-connection model with a thread-per-connection architecture using Rust threads, aiming to improve concurrency, reduce connection overhead, and provide built-in connection pooling.

  • Performance Claims: The project claims potential performance improvements of 50% to 300x for certain workloads, though developers and commenters remain skeptical, viewing it primarily as an AI-assisted experiment rather than a production-ready replacement.

You can check out the source code in the pgrust GitHub repository or try it out directly on the pgrust website.

malisper/pgrust: Postgres rewritten in Rust, now passing 100% of the Postgres regression tests @GitHub

The goal is to make Postgres easier to change from the inside: keep the behavior Postgres-shaped, keep the real Postgres tests as the oracle, and use Rust plus AI-assisted programming to explore deeper server changes.

pgrust — postgres, rewritten in rust


Rebuilding Postgres for 300x faster analytics: batching, operator fusion, and SIMD - malisper.me

The article details how pgrust achieved a 300x speedup over PostgreSQL on analytical database benchmarks (Clickbench) by optimizing its query engine.

While PostgreSQL was designed in the 1980s when disk I/O was the primary bottleneck, modern hardware makes CPU and memory bandwidth the main performance constraints. To address this, pgrust improves upon Postgres's traditional Volcano execution model—which processes data one row at a time with significant function call overhead—by applying three key techniques:

  • Batching: Processes rows in fixed-size batches (e.g., 1024 items at a time) using stack-allocated buffers. This eliminates per-row call overhead and avoids costly memory allocations, speeding up execution by ~2.7x over the basic Volcano model.

  • Operator Fusion: Combines separate query plan operations (such as a sequential scan and an aggregation sum) into a single loop to eliminate array-copying overhead.

  • SIMD (Single Instruction, Multiple Data): Utilizes hardware-level vector instructions to execute arithmetic operations across multiple values simultaneously, driving performance nearly 10x faster than the initial Volcano setup.

Overall, applying these optimizations reduced the benchmark execution time from 1.3 seconds down to 135 ms (compared to ~20 seconds in standard PostgreSQL).



WikiArt

WikiArt - Wikipedia 
WikiArt (formerly known as WikiPaintings) is a visual art wiki, active since 2010.

WikiArt.org - Visual Art Encyclopedia

what is wikiart - Google Search

WikiArt is an online, community-driven visual art encyclopedia. It features over 250,000 artworks by thousands of artists, covering everything from cave paintings to contemporary works. It is a highly popular digital resource for art study, educational research, and inspiration. [1, 2, 3]

Key Features of WikiArt

  • Vast Categorization: You can browse artwork at scale by filtering through distinct artists, styles, art movements, genres, and even specific museums.
  • Multinational Reach: The site hosts pieces from artists across more than 100 countries and the interface supports multiple languages.
  • Fair Use Policy: WikiArt acts as a non-profit project. It features works in the public domain as well as copyright-protected art, the latter of which is showcased for educational and informational purposes under fair use. [4, 5]
How the Community Uses It

Because it functions like a wiki, much of the metadata and translations are contributed by volunteer art enthusiasts and experts around the globe. While some users reference it merely for casual browsing and educational purposes, it is also highly utilized by artificial intelligence researchers as a curated, expansive dataset for training computer vision and AI art models. [2, 3, 5, 6]


 Niagara, 1857 - Frederic Edwin Church - WikiArt.org


Public domain

Lovable: AI vibe coding apps

 what is lovable company - Google Search

Lovable is a Swedish AI software startup that pioneered "vibe coding"—a concept where users can build, deploy, and iterate fully functional web apps and websites simply by chatting with an AI in plain English. [1, 2, 3]

Founded in Stockholm in 2023 by Anton Osika and Fabian Hedin, the company grew out of the popular open-source tool GPT Engineer. It allows individuals and enterprise teams to generate production-ready software—managing front-end, back-end logic, databases, and integrations—without needing to write any manual code. [1, 2, 4]

Check out their platform on Lovable to build apps, or read their Vision to learn more about how they aim to democratize software creation. [5]

[1] https://en.wikipedia.org/wiki/Lovable_(company)[2] https://www.crunchbase.com/organization/lovable-803a
[3] https://app.dealroom.co/companies/lovable
[4] https://techcrunch.com/2025/02/25/swedens-lovable-an-app-building-ai-platform-rakes-in-16m-after-spectacular-growth/
[5] https://www.youtube.com/watch?v=5FWO5n5VTQc


//lovable.dev/ 
AI App Builder | Vibe Code Apps & Websites with AI, Fast

Lovable Pricing: 0, 25, 50, enterprise / month

In 2023, Anton Osika developed GPT Engineer, open-source software that used large language models to code software applications. 

AntonOsika/gpt-engineer: CLI platform to experiment with codegen. Precursor to: https://lovable.dev @GitHub


what technology is used for lovable.app generated apps - Google Search

Lovable (formerly GPT Engineer) generates full-stack web applications using industry-standard modern technology stack. The platform creates the frontend using React, Vite, and TypeScript, styled using Tailwind CSS. For the backend, it utilizes Supabase to handle databases, authentication, storage buckets, and edge functions. [1, 2, 3, 4, 5]

Key technology components of a Lovable-generated app include:

  • Frontend Framework: React with Vite for fast bundling and hot module reloading.
  • Language: TypeScript to ensure type safety and maintainability.
  • Backend & Database: Supabase (which operates on top of PostgreSQL) for serverless backend logic and scalable databases.
  • Authentication: Pre-built login, signup, and user session management powered by Supabase Auth.
  • Styling: Tailwind CSS for fast, responsive, and customizable UI design. [2, 3, 4, 6, 7]
Generated code can be previewed directly in the browser and synced to GitHub for further deployment and engineering workflows. [4, 8]

[1] https://lovable.dev/guides/rapid-application-development-tools



Former Intel CEO on What Went Wrong, What's Next + Lovable CEO on the Real Promise of Vibe Coding - YouTube

Lovable is an AI-native "vibe coding" platform that allows anyone—including non-technical users—to build full-stack web applications and websites entirely through natural language prompts.

Founded by CEO Anton Osika and Fabian Hedin, the Stockholm-based startup has quickly become one of the fastest-growing software companies in tech history.


  • The Core Product: Lovable targets "the other 99%" who don't have a formal computer science background. Users describe what they want to create (or upload design screenshots) and the AI automatically handles the underlying frontend, backend, and hosting infrastructure.

  • Hyper-Growth Metrics: The company is sprinting toward $1 billion in annual recurring revenue (ARR), having reached $100 million ARR within eight months of crossing its first million, and hitting $400 million by early 2026.

  • Funding & Valuation: Following massive funding rounds from top-tier VCs like Accel, DST Global, Khosla Ventures, and Salesforce Ventures, Lovable is valued at roughly $6.6 billion.

  • The "Vibe Coding" Movement: Alongside tools like Cursor and Replit, Lovable is pioneering a shift in software development where curiosity and product iteration speed are prioritized over traditional coding credentials.