데이터 · GitHub

SawitDB: The First Agricultural-Based Database with Anti-Corruption Protocols. Built for Data Sovereignty to oppose expensive, unreliable state infrastructure.

• Hybrid Paged Architecture: Data is stored in 4096-byte binary pages, but hot data is cached as native Objects for zero-copy reads.
• Single File Storage: All data, schema, and indexes are stored in a single .sawit file.

Relational messaging database schema for one-to-one and group chat apps with attachments and MySQL Workbench model.

• One-to-one conversation support.
• Group chat support.

支持连表查询的mybatis-plus,mybatis-plus风格的连表操作提供left join、right join等操作

基于SpringBoot2.x、SpringCloud和SpringCloudAlibaba并采用前后端分离的企业级微服务多租户系统架构。并引入组件化的思想实现高内聚低耦合，项目代码简洁注释丰富上手容易，适合学习和企业中使用。真正实现了基于RBAC、jwt和oauth2的无状态统一权限认证的解决方案，面向互联网设计同时适合B端和C端用户，支持CI/CD多环境部署，并提供应用管理方便第三方系统接入；同时还集合各种微服务治理功能和监控功能。模块包括:企业级的认证系统、开发平台、应用监控、慢sql监控、统一日志、单点登录、Redis分布式高速缓存、配置中心、分布式任务调度、接口文档、代码生成等等。

A cloud-native database based on PostgreSQL developed by Alibaba Cloud.

유연하고 강력한 Python용 데이터 분석 및 조작 라이브러리로, R의 data.frame 객체와 유사한 레이블이 지정된 데이터 구조와 통계 함수 등을 제공합니다

• Easy handling of missing data (represented as NaN, NA, or NaT) in floating point as well as non-floating point data
• Size mutability: columns can be inserted and deleted from DataFrame and higher dimensional objects

Add your HDD, SSD and NVMe drives to your Synology's compatible drive database and a lot more

Building Convolutional Neural Networks From Scratch using NumPy

A simple and easy to use Data Validation library for Python.

Event-driven OneLake pipeline desktop tool with auto-merge Upsert, Python reporting, and Teams alert

• Event-driven trigger: A OneLake FileCreated event on the Files/inbox folder launches the pipeline automatically as soon as a .csv file lands, with a filter matching files whose subject ends in .csv. No schedule, no manual invocation.
• Filename resolution from the event: A Set variable activity extracts the file name from the trigger event payload, falling back to a pipeline parameter when the run is started manually. The resolved value is reused by every downstream activity.

An observability database aims to ingest, analyze and store Metrics, Tracing and Logging data.

Event-driven OneLake pipeline with automated Upsert merge and Python reporting

• Event-driven orchestration: A trigger bound to OneLake file-created events watches the designated inbox folder and launches the pipeline automatically the moment a matching file lands. No scheduler, no manual run, no polling loop; the arrival of data is itself the execution signal.
• Parameterless-by-design entry point: The trigger event carries the file name through to the pipeline, where a variable resolution step coalesces the event payload with an optional manual parameter. The same pipeline supports both automatic and on-demand invocation without code changes or duplicated definitions.

A simple CLI for SQL databases

Dataform Tools - VS Code extension to run and visualise Dataform data pipelines and much more

• Compiled query and dry run - ✅ - ✅ - Beside the file on save, with the size and cost of a dry run and the schema of the result
• Errors in the editor - ✅ - ✅ - Compile errors and BigQuery's dry-run errors, on the line you wrote

Easy full stack backup operations on UNIX-like systems.