--- title: "🛠️ OpenIDEA opens 770 files in just 1.1 seconds: IntelliJ feel without the JVM burden｜Open Source Finds Daily" description: "A new project that shot to 7.2k stars within 30 days, with a README that posts benchmarks taking aim at its own predecessor: OpenIDEA opens a project like freqtrade, roughly 770 Python files, and is ready in just 1.1 seconds using 169 MB, versus IntelliJ IDEA 2026.2.3 at 13.2 seconds and 2011 MB." canonical_url: "https://blog.markkulab.net/en/open-source-weekly/open-source-weekly-2026-11-06" author: "Mark Ku" author_url: "https://blog.markkulab.net/en/author/mark-ku" site: "Mark Ku's Tech Notes" date_published: "2026-11-06T02:00:00.000Z" category: "Daily Open Source Finds" tags: ["open-source", "podcast", "開源工具", "開源", "OpenIDEA", "Mika", "auto-ontology", "NVIDIA", "IntelliJ", "Rust", "Tauri"] language: "en" license: "CC BY 4.0" license_url: "https://creativecommons.org/licenses/by/4.0/" attribution: "when reusing or quoting, credit the author and link back to the original" --- # 🛠️ OpenIDEA opens 770 files in just 1.1 seconds: IntelliJ feel without the JVM burden｜Open Source Finds Daily ## Opening A brand-new project that rocketed to 7.2k stars in 30 days, with a README that benchmarks itself directly against its elders: open freqtrade (a Python project with roughly 770 files) in OpenIDEA and it's ready in 1.1 seconds using 169 MB, versus IntelliJ IDEA 2026.2.3 at 13.2 seconds and 2011 MB. I'm Muyan, and today we also have Mika, an Android agent you'd actually dare install on your daily driver, plus auto-ontology, NVIDIA's official open source release that pulled 289 points on Hacker News. I'll explain shortly how it teaches a text-to-SQL agent to say "I can't answer that." ## Today's Open Source Picks ### 1. OpenIDEA: Keep IntelliJ's muscle memory, drop the JVM startup and memory bill - **What it is**: Every Java/Kotlin developer lives with the same contradiction: IntelliJ's shortcuts and tool windows are already wired into your fingers, but waiting for indexing every day and watching gigabytes of RAM disappear gets old fast. OpenIDEA ports IDEA's entire interaction model over (keymap, tool windows, search-everywhere) but wraps it in a lightweight native shell. Built for people who don't want to relearn shortcuts and are done with startup times. - **Recent buzz**: 7,251 GitHub stars, a project that appeared within the last 30 days, Apache-2.0 licensed, primarily TypeScript. HN has an entire thread arguing over whether it counts as "rebuilt in Rust." - **Standout features**: A single app containing the editor, code insight, debugger, Git, terminal, database client, and HTTP client, supporting 60+ languages with builds for all three platforms. The README includes the benchmark numbers above and, refreshingly honestly, notes that "IDEA performs deeper Python analysis, so 'ready' doesn't mean both are doing the same work." It also ships perf/compare so you can rerun everything on your own machine. - **Getting started**: The fastest path is grabbing the installer for your platform from GitHub Releases: macOS, Windows, and Linux are all covered. To build it yourself, run `pnpm install && pnpm tauri dev`; you'll need Rust 1.96, Node 22, and the Tauri prerequisites. - **Versus the alternatives**: Zed and Lapce, the other Rust-family editors, render their entire UI in Rust. OpenIDEA goes the Tauri route: a Rust core with a WebView/TypeScript frontend, which is exactly why some HN commenters feel "rebuilt in Rust" oversells it. I think that criticism is fair, but the real selling point was never pure Rust anyway, it's "IDEA's feel in a lightweight shell." The README also states plainly that the project is unaffiliated with JetBrains, so don't treat it as a feature-equivalent IDEA replacement. - **Who it's for**: Anyone who can't live without IntelliJ shortcuts but whose main machine is running out of memory. - **Link**: https://github.com/l0ng-ai/openidea ### 2. Mika: A computer-use agent running inside your phone, with no official server - **What it is**: A mobile computer-use agent. It opens apps, taps, types, and scrolls on a hidden background virtual display while you keep using your phone normally; pop open a small window anytime to watch progress live. Built for people who want to automate phone tasks but balk at handing their screen contents to some vendor's backend. - **Recent buzz**: 7,301 GitHub stars, also a project from the last 30 days, Apache-2.0, primarily Kotlin, fully open source. - **Standout features**: It works by "looking at the screen and finding buttons" via accessibility, so apps don't need to expose an API and there are no per-app integrations to build; any app or website works. A built-in browser lets you issue commands against the current page, and it stops the moment you touch the screen. It remembers preferences you've mentioned and distills completed tasks into skills, so repeat runs get faster and more reliable. - **Getting started**: Download the APK from Releases (Android 11+), go to Settings › Model to pick a provider and enter your API key, then run the "Set up phone control" wizard once to pair wireless debugging. If you only want chat, web, and file features, you can skip step three. The README even provides a command that lets an AI agent on your computer set the whole thing up for you. - **Versus the alternatives**: Unlike mobile agent services that ship your screen to a vendor cloud, Mika has no backend of its own; the agent loop runs locally on the phone. It's also not limited to first-party apps the way built-in vendor assistants are. But let's be clear about the catch: no Mika server doesn't mean fully offline, since the model still comes from your own API key or a ChatGPT/xAI/OpenRouter account. And letting it tap your screen requires enabling accessibility and pairing wireless debugging, which are substantial permissions. Think it through before installing. - **Who it's for**: Self-hosting Android users who worry about data leaving their device but still want to offload repetitive phone tasks. - **Link**: https://github.com/wangzan101/Mika ### 3. NVIDIA auto-ontology: Getting data agents to admit "I can't answer that" - **What it is**: Anyone who's built text-to-SQL or data agents has hit the same wall: the agent answers fast and confidently, and the answer is wrong. auto-ontology automatically compiles an ontology layer from database metadata, mapping business terms to columns, measures to vetted SQL, and relationships between tables. The agent queries this semantic graph instead of guessing. Built for teams actually connecting agents to production databases inside an enterprise. - **Recent buzz**: 289 points and 139 comments on Hacker News, 8,260 GitHub stars, officially open sourced by NVIDIA, Apache-2.0, primarily Python. - **Standout features**: An answerability check that first determines whether a question can be answered at all, and if not, has the agent ask a follow-up instead of confidently making things up. Every answer comes with the SQL and the agent's steps. The same context can be fed to any agent harness via MCP, agent skills, or the REST API, while definitions can be manually reviewed and certified in the Web UI or via API. There's also a companion auto-ontology-eval repo that runs same-model, two-prompt experiments comparing "schema stuffed into the prompt" against "going through the ontology" on BIRD, BEAVER, FDABench-Lite, and Wide World Importers, scored with deterministic verifiers. This benchmark suite is the vendor's own repo, so treat it as a reproducible methodology rather than third-party validation. - **Getting started**: The repo includes a Dockerfile, docker-compose.yml, and a helm chart. Clone `.env.example`, run `docker compose` to spin up a service alongside your database, then point your agent at the MCP endpoint and you're done. - **Versus the alternatives**: The most common homegrown approach is pasting the entire schema into the context window, where tokens grow linearly with tables and columns, and joins and measures get improvised by the agent every single time. auto-ontology instead gives the agent tools to query the ontology and pull only the terms and tables relevant to the question at hand. It can also import your existing semantic model; it's positioned to complement semantic layers you already have like dbt and Cube, not replace them. - **Who it's for**: Data engineering teams sitting on a pile of tables and suffering through agent-generated garbage SQL. - **Link**: https://github.com/NVIDIA/auto-ontology ## Closing Today's three picks share an obvious theme: replacing "the model just guesses" with "there's structure to query." OpenIDEA strips out the IDE's weight while preserving its interaction habits, Mika pulls the agent back onto your own device, and auto-ontology lays down a queryable semantic map for agents. If you forced me to pick one to install tonight, it's OpenIDEA: downloading an installer is the lowest-cost commitment, and since the README ships perf/compare, you can verify that 1.1 second figure on your own project. One note: the release dates for these three projects weren't confirmed in the material I had, and the star counts are snapshots from when I did the research, so check the repos for current numbers. See you tomorrow. --- ## About this article and its author Originally published on [Mark Ku's Tech Notes](https://blog.markkulab.net/en/open-source-weekly/open-source-weekly-2026-11-06) License: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — when reusing or quoting, credit the author and link back to the original ### About the author **[Mark Ku](https://blog.markkulab.net/en/author/mark-ku)** — Software engineer - 10+ years as a software engineer - Built North-American e-commerce and AI SaaS subscription billing ### Free tools built by the author All of these are free to use: - [Free PDF Sign Tool](https://blog.markkulab.net/en/tools/pdf-sign): Online PDF sign tool — draw, type, or upload a signature, then drag, resize, and download. Everything runs in your browser; nothing is uploaded. - [VS Code Refactory](https://blog.markkulab.net/en/tools/refactory): Refactory is a VS Code refactoring extension: 34 actions plus a 37-rule code-smell inspection layer with a Code Health dashboard, across 18 languages, backed by 534 tests. It learns your repo's conventions: where interfaces live, where DI is registered, whether 'use client' belongs. It ranks files by git churn × complexity so you know what to fix first, and hands any smell to the Claude Code already on your machine. Free to use, and your source never leaves your computer. - [DB-Kit Database Manager](https://blog.markkulab.net/en/tools/db-kit): DB-Kit is a lightweight, cross-platform database manager built with Tauri + Rust + React. Manage MySQL, MariaDB, PostgreSQL, SQL Server, Oracle, SQLite, MongoDB, Redis, Kafka, Elasticsearch and RabbitMQ from one consistent interface: passwords encrypted in the OS keychain, SSH tunnels, full CRUD, a visual query builder, stacked multi-statement result sets, cross-connection data transfer, schema & data compare with sync SQL and schema snapshots, Excel / CSV import & export, visualized execution plans, ER diagrams, scheduled backups, SQL stress testing with p50–p99 latency percentiles, a 15-rule SQL review engine, Review & Run (AI review plus per-statement backups and an auto-generated rollback script), Kafka message browsing with monitoring & alerts, an SSH terminal with SFTP / FTP, Docker / Kubernetes, remote desktop (RDP / VNC / RustDesk), file / folder compare, stored procedure integration tests, six UI languages, a built-in AI assistant (a local CLI or any Anthropic / OpenAI-compatible API; natural-language SQL, AI review and tuning advice) and the dbk CLI. Free and open source (MIT), with installers for Windows, macOS and Linux. - [VS Code Super Mermaid](https://blog.markkulab.net/en/tools/super-mermaid): Super Mermaid is a VS Code extension for beautiful Mermaid diagrams out of the box: auto-colored live preview, mouse pan & zoom, high-res PNG / SVG export, 21 templates and multiple themes. Free and open source (MIT). - [React Super Mermaid](https://blog.markkulab.net/en/tools/react-super-mermaid): react-super-mermaid is an open-source React component library: render beautiful Mermaid diagrams with a single , with built-in colorful / sketch themes, pan & zoom, in-diagram search, and high-res SVG / PNG export. Lightweight, SSR-safe, fully typed. Free and open source (MIT). - [Jira / Confluence Super Mermaid](https://blog.markkulab.net/en/tools/jira-super-mermaid): An Atlassian Forge app: write Mermaid syntax directly inside a Jira issue or a Confluence page and get flowcharts, sequence diagrams, state machines and Gantt charts. 11 diagram types, SVG / PNG export, light and dark themes, full CJK support. Runs on Atlassian: your diagrams live in your own site and the app calls no third-party service. Free, coming soon to the Atlassian Marketplace. - [Mermaid Live Preview](https://blog.markkulab.net/en/tools/mermaid-preview): Write Mermaid in your browser, see it render instantly, and share the whole diagram as a single link. No sign-up, nothing uploaded to a server, and mermaid.live share links work as-is. - [React Intl Phone Number](https://blog.markkulab.net/en/tools/react-intl-phone-number): react-intl-phone-number is an open-source React component: framework-agnostic and antd-free, with E.164 in/out, a searchable flag / country-code dropdown, configurable validation levels (strict / mobile-strict / loose), themeable CSS, and i18n — phone logic powered by google-libphonenumber. Lightweight and fully typed. Free and open source (MIT). - [Uptime Kuma Cluster](https://blog.markkulab.net/en/tools/uptime-kuma-cluster): Turn single-node Uptime Kuma into a highly available cluster: OpenResty + Lua smart load balancing, shared MariaDB state, health checks and automatic failover, plus cluster-management REST APIs. One Docker Compose command to start. Free and open source (MIT). - [AI Podcast Cut](https://blog.markkulab.net/en/tools/ai-podcast-cut): Drop in a recording and it removes fillers and stutters, levels loudness segment by segment, and sends a second agent to review every cut. Cut points snap to word boundaries and zero crossings, every splice gets a fade, and sentence-end breaths are preserved. Desktop app for Windows, macOS and Linux. MIT licensed; the Windows installer bundles ffmpeg. - [AI Video Cut](https://blog.markkulab.net/en/tools/ai-video-cut): Pick something in your video: type it (face, license plate, phone screen, logo), click points or drag a box, or let Claude Code / Codex pick it. AI Video Cut tracks it frame by frame, then mosaics or blurs it, recolors it, pins stickers and text to it, swaps a screen or poster for your own image or video, or removes it using background that other frames actually captured. Plus sequence editing, local captions and an AI assistant. Free, open-source (MIT) Windows desktop app (macOS / Linux experimental) that runs locally, nothing uploaded. - [open-pos restaurant POS](https://blog.markkulab.net/en/tools/open-pos): One computer and one receipt printer is enough to open the shop. Your data lives on your own disk, no subscription, no lock-in, MIT licensed. Money is integer New Taiwan dollars with tax split by the statutory formula, so sales + tax always equals the total. Printing goes straight over ESC/POS on TCP 9100, with no vendor driver. Tauri + Rust + SQLite desktop app, v1.0 in development. - [.NET e-commerce API template](https://blog.markkulab.net/en/tools/dotnet-ecommerce-api): An e-commerce backend API template built on .NET 10: Controller → Service → Repository layering, Autofac convention-based registration, SqlSugar for MySQL / MariaDB and SQL Server, Redis cache and message queue, Hangfire jobs, JWT auth, and an extensible payment provider module (ECPay, Newebpay). Apache 2.0. - [Open Token Monitor team AI usage](https://blog.markkulab.net/en/tools/open-token-monitor): Collect token usage and equivalent cost from every employee's AI coding tools into a hub you host yourself: PostgreSQL, org roster, dashboards compared by company and department, and a reports API. Electron and Rust/Tauri clients upload every 30 minutes. MIT licensed, one Docker command. - [ai-security-monitor defensive security](https://blog.markkulab.net/en/tools/ai-security-monitor): Your website is live. Who checks its certificates, security settings and known vulnerabilities? A self-hosted Security Hub brings website scans and host monitoring together, deduplicates findings and compares scans after fixes. ### Daily podcasts - [Mark's Tech Insights — Daily AI News](https://blog.markkulab.net/en/category/tech-news): Daily curated AI and tech trends. 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