Ultra fast and easy duplicate file finder. Awesome TUI/GUI to manage results.
The KD Files - Case File Tracker
The Zellij Filepicker
Explore the Zellij filepicker plugin. Learn dynamic filesystem traversal with fuzzy finding for faster file navigation and workflows.
Spacedrive — A local-first data engine for everything you own
Index any data source. Search everything from one place. Keep it on your machine.
shshemi/tabiew
A lightweight TUI application to view and query tabular data files, such as CSV, TSV, and parquet.
GitHub - clarisma/geodesk: Fast and storage-efficient spatial database engine for OpenStreetMap data
Fast and storage-efficient spatial database engine for OpenStreetMap data - clarisma/geodesk
GitHub - hmans/beans: A CLI-based, flat-file issue tracker for humans and robots. 🤖
A CLI-based, flat-file issue tracker for humans and robots. 🤖 - hmans/beans
turbopuffer: fast search on object storage
Inaugural blog post about the development of turbopuffer, a search engine that uses object storage and SSD caching for cost-effective, low latency search. This post describes into the motivation behind its creation, its unique architecture, and how it significantly reduces costs for large-scale vector searches. Discover how turbopuffer is transforming search infrastructure for companies like Cursor and Suno, offering a scalable and reliable solution.
ParadeDB — Search without a second system
One Postgres for your application data, full-text search, vector retrieval, and aggregations. Home of the pg_search extension.
JuiceFS - Open Source Distributed POSIX File System for Cloud
JuiceFS is a cloud-based high-performance distributed file system, based on object storage and database to achieve data and metadata separation architecture, easily carrying tens of billions of file storage, to meet the random read performance requirements of big data, AI, autonomous driving, gene sequencing and other massive data.
OneCommander | Fast Windows File Manager
A modern dual-pane file manager for Windows 11 and 10 with tabs, Miller columns, themes, and no ads.
Structured merge with auto-tuning: balancing precision and performance
Software-merging techniques face the challenge of finding a balance between precision and performance. In practice, developers use unstructured-merge (i.e., line-based) tools, which are fast but imprecise. In academia, many approaches incorporate information on the structure of the artifacts being merged. While this increases precision in conflict detection and resolution, it can induce severe performance penalties. Striving for a proper balance between precision and performance, we propose a structured-merge approach with auto-tuning. In a nutshell, we tune the merge process on-line by switching between unstructured and structured merge, depending on the presence of conflicts. We implemented a corresponding merge tool for Java, called JDime. Our experiments with 8 real-world Java projects, involving 72 merge scenarios with over 17 million lines of code, demonstrate that our approach indeed hits a sweet spot: While largely maintaining a precision that is superior to the one of unstructured merge, structured merge with auto-tuning is up to 12 times faster than purely structured merge, 5 times on average.
tobi/qmd
mini cli search engine for your docs, knowledge bases, meeting notes, whatever. Tracking current sota approaches while being all local