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7 repositorios

Awesome GitHub RepositoriesSQL Server Persistence

Integration for storing application state and definitions in Microsoft SQL Server.

Distinct from SQL Server Connectors: Shortlist candidates focus on enterprise platforms or Java clients rather than a generic persistence provider for the engine.

Explore 7 awesome GitHub repositories matching data & databases · SQL Server Persistence. Refine with filters or upvote what's useful.

Awesome SQL Server Persistence GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • alibaba/dataxAvatar de alibaba

    alibaba/DataX

    17,241Ver en GitHub↗

    DataX is a distributed data integration framework and plugin-based ETL tool designed for synchronizing large datasets between heterogeneous sources and destinations. It functions as a JDBC data migration engine and offline synchronization tool, enabling the movement of data between relational databases, NoSQL stores, and object storage. The system utilizes a plugin-based connector architecture that decouples reader and writer logic, allowing it to map and transform data types across different storage engines using a standardized internal representation. This design supports heterogeneous data

    Reads records from remote SQL Server databases using JDBC connections and SQL SELECT statements.

    Java
    Ver en GitHub↗17,241
  • microsoft/sql-server-samplesAvatar de microsoft

    microsoft/sql-server-samples

    11,122Ver en GitHub↗

    This is a reference implementation library providing a collection of code samples, Transact-SQL scripts, and schemas for SQL Server, Azure SQL, and Azure Synapse. It focuses on providing standardized implementation patterns and reference code for building relational databases and cloud data warehouses. The library distinguishes itself by offering specialized guides and examples for deploying database instances within containerized environments and Azure cloud services. It includes specific reference databases and language extensions for integrating machine learning services and advanced analy

    Provides reference code and T-SQL patterns for structuring relational databases and warehouses.

    Ver en GitHub↗11,122
  • elsa-workflows/elsa-coreAvatar de elsa-workflows

    elsa-workflows/elsa-core

    7,629Ver en GitHub↗

    Elsa Core is a workflow engine framework designed for defining, executing, and managing long-running business processes. It functions as a distributed workflow orchestrator and event-driven trigger system, capable of operating as a multi-tenant platform with secure data isolation. The project distinguishes itself through a flexible approach to workflow definitions, supporting a visual drag-and-drop designer, programmatic C# definitions, and portable JSON specifications. It provides a highly extensible architecture allowing for the development of custom activities and the use of a dynamic expr

    Persists workflow definitions and runtime state in SQL Server for transactional consistency.

    C#csharpdotnetelsa
    Ver en GitHub↗7,629
  • feast-dev/feastAvatar de feast-dev

    feast-dev/feast

    6,727Ver en GitHub↗

    Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma

    Points to a Microsoft SQL Server table or query as the origin for feature data.

    Pythonbig-datadata-engineeringdata-quality
    Ver en GitHub↗6,727
  • dlt-hub/dltAvatar de dlt-hub

    dlt-hub/dlt

    5,472Ver en GitHub↗

    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.

    Enables the retrieval of records from relational databases via connectivity plugins for target loading.

    Pythondatadata-engineeringdata-lake
    Ver en GitHub↗5,472
  • brentozarultd/sql-server-first-responder-kitAvatar de BrentOzarULTD

    BrentOzarULTD/SQL-Server-First-Responder-Kit

    3,832Ver en GitHub↗

    This project is a collection of specialized toolsets for SQL Server, functioning as a diagnostic toolkit, performance monitor, and database administrator framework. It provides stored procedures and utilities designed to automate backup recovery, diagnose system health, and optimize database performance and indexing. The kit distinguishes itself through specialized capabilities for point-in-time restoration and the calculation of estimated data loss windows using backup history. It also includes an index optimizer that analyzes usage and size to provide prioritized recommendations for data re

    Provides a collection of stored procedures for analyzing health, performance, and configuration issues.

    TSQLfirst-responder-kithealth-checksmicrosoft-sql-server
    Ver en GitHub↗3,832
  • go-gorp/gorpAvatar de go-gorp

    go-gorp/gorp

    3,751Ver en GitHub↗

    Gorp is a lightweight object-relational mapper for Go that binds structs to relational database tables. It functions as a relational data mapper and SQL dialect abstraction layer, automating the translation between application data and relational rows. The project provides a translation layer that generates vendor-specific SQL for PostgreSQL, MySQL, SQLite, Oracle, and SQL Server. It distinguishes itself by implementing optimistic locking via version columns to prevent concurrent update conflicts and providing a database schema generator to create tables and indexes from object definitions.

    Maps Go primitive types and structs to Microsoft SQL Server data types.

    Go
    Ver en GitHub↗3,751
  1. Home
  2. Data & Databases
  3. SQL Server Persistence

Explorar subetiquetas

  • Database-Specific Type MappingsMapping of a specific database's native types into a standardized format. **Distinct from SQL Server Persistence:** Distinct from SQL Server Persistence: focuses on type conversion for processing rather than storage implementation.
  • Diagnostic ToolkitsCollections of stored procedures for assessing server health and performance. **Distinct from SQL Server Persistence:** Distinct from persistence providers: focuses on diagnostic and administrative stored procedure suites rather than application state storage.
  • SQL Server Data Sources1 sub-etiquetaPointing to a Microsoft SQL Server table or query as the origin for feature data used in training or serving. **Distinct from SQL Server Persistence:** Distinct from SQL Server Persistence: focuses on using SQL Server as a data source for feature retrieval, not general application state persistence.