Fast, secure, efficient backup program
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Updated
Jun 22, 2023 - Go
Entity resolution (also known as data matching, data linkage, record linkage, and many other terms) is the task of finding entities in a dataset that refer to the same entity across different data sources (e.g., data files, books, websites, and databases). Entity resolution is necessary when joining different data sets based on entities that may or may not share a common identifier (e.g., database key, URI, National identification number), which may be due to differences in record shape, storage location, or curator style or preference.
Fast, secure, efficient backup program
Deduplicating archiver with compression and authenticated encryption.
Prometheus Alertmanager
Cross-platform backup tool for Windows, macOS & Linux with fast, incremental backups, client-side end-to-end encryption, compression and data deduplication. CLI and GUI included.
A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data.
Extremely fast tool to remove duplicates and other lint from your filesystem
A powerful duplicate file finder and an enhanced fork of 'fdupes'.
Simple, configuration-driven backup software for servers and workstations
A fast high compression read-only file system
rustic - fast, encrypted, and deduplicated backups powered by Rust
Config driven, easy backup cli for restic.
A powerful and modular toolkit for record linkage and duplicate detection in Python
Data deduplication engine, supporting optional compression and public key encryption.
Scalable identity resolution, entity resolution, data mastering and deduplication using ML
Fast, accurate and scalable probabilistic data linkage using your choice of SQL backend
Straightforward fuzzy matching, information retrieval and NLP building blocks for JavaScript.
Коллекция готовых SQL запросов для PostgreSQL по часто возникающим задачам (получение и модификация данных, ускорение запросов, обслуживание БД)
A list of free data matching and record linkage software.
Locality Sensitive Hashing using MinHash in Python/Cython to detect near duplicate text documents
Created by Halbert L. Dunn
Released 1946