5 repositorios
Capabilities that allow external data processing frameworks and streaming services to write directly into tables.
Distinguishing note: Existing candidates focus on network socket buffering or data enrichment rather than writing from compute frameworks to tables.
Explore 5 awesome GitHub repositories matching data & databases · External Data Writing. Refine with filters or upvote what's useful.
Delta is a lakehouse table format that brings ACID transactions and data warehouse consistency to large scale data lakes on cloud object storage. It serves as an ACID transaction manager, coordinating atomic commits and serializable isolation for concurrent reads and writes across distributed compute engines. The project provides a multi-engine interoperability layer that uses format translation to allow diverse SQL engines and processing frameworks to read and write the same tables. It functions as a data versioning system, utilizing a transaction log to enable time travel, historical snapsh
Connects data processing frameworks and streaming services to write data directly into tables.
Moto is a cloud service mockery framework and API mock server that simulates AWS infrastructure locally. It allows developers to test cloud-dependent code and verify infrastructure-as-code templates without deploying real resources or incurring costs. The project functions as an SDK interceptor that can patch existing service clients to redirect requests to a local mock environment. It can also be run as a standalone HTTP server, enabling any programming language to interact with the simulated endpoints. The framework covers a vast array of simulated capabilities, including data storage, com
Simulates the process of writing data records from external sources into database tables.
Updates an existing record in an external database with fields generated by an agent.
dlt es una herramienta de ingesta de datos en Python y framework de pipeline ETL diseñado para obtener datos de diversas fuentes y persistirlos en destinos estructurados. Funciona como un motor de inferencia de esquemas que detecta automáticamente tipos de datos y aplana estructuras JSON anidadas en tablas relacionales, moviendo datos desde fuentes a lakehouses, almacenes de datos o bases de datos vectoriales. El proyecto destaca por la generación de pipelines impulsada por IA, utilizando modelos de lenguaje de gran tamaño para crear código de extracción y conectores para APIs REST. También admite almacenamiento vectorial multimodal y población especializada de bases de datos vectoriales para soportar aplicaciones de IA y machine learning. El framework cubre una amplia gama de capacidades, incluyendo evolución automática de esquemas, carga incremental de datos mediante seguimiento de estado y validación de calidad de datos mediante la aplicación de contratos de datos. Proporciona herramientas para la normalización de datos relacionales, transformaciones pre y post-carga, y una variedad de adaptadores de destino para bases de datos SQL y almacenes de objetos en la nube. La observabilidad se maneja a través de paneles de ejecución de pipelines, seguimiento de linaje de columnas y verificación de versiones de esquema mediante hashes basados en contenido.
Provides capabilities to control if new data replaces existing sets, appends, or merges based on keys.
XlsxWriter is a library for generating spreadsheets in the XLSX format, functioning as an Excel workbook writer and file generator. It provides the capability to write data, apply cell formatting, and build complex layouts across multiple worksheets. The project distinguishes itself with a memory-optimized writing mode that flushes large datasets to disk row-by-row, enabling the creation of files exceeding 4 GB while minimizing RAM consumption. It also includes a specialized mechanism for embedding binary project files and digital signatures to enable VBA macros and signed scripts within work
Provides type-specific methods for writing strings, numbers, and formulas into spreadsheet cells.