Found 42 packages
Microsoft Azure Storage DataMovement Library offers a set of APIs extending the existing Azure Storage .Net Client Library to help customer transfer Azure Blob and File Storage with high-performance, scalability and reliability. For this release, see notes - https://github.com/Azure/azure-storage-net-data-movement/blob/master/README.md and https://github.com/Azure/azure-storage-net-data-movement/blob/master/changelog.txt Microsoft Azure Storage team's blog - http://blogs.msdn.com/b/windowsazurestorage/
This client library is the base package for the Azure Storage Data Movement library. The Azure Storage Data Movement library is designed for high-performance, multi-threaded uploading, downloading and copying Azure Storage blobs and files. This library is inteneded to be used with one or more of the Data Movement sub-packages, such as Azure.Storage.DataMovement.Blobs or Azure.Storage.DataMovement.Files.Shares. For this release see notes - https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/storage/Azure.Storage.DataMovement/README.md and https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/storage/Azure.Storage.DataMovement/CHANGELOG.md
This client library enables high-performance, multi-threaded uploading, downloading and copying Azure Storage blobs and containers. The package depends on the Azure.Storage.DataMovement package and can be used in conjuction with other Data Movement sub-packages, such as Azure.Storage.DataMovement.Files.Shares to transfer data between services. For this release see notes - https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/storage/Azure.Storage.DataMovement.Blobs/README.md and https://github.com/Azure/azure-sdk-for-net/blob/master/sdk/storage/Azure.Storage.DataMovement.Blobs/CHANGELOG.md
This client library enables high-performance, multi-threaded uploading, downloading and copying Azure File Share files and directories. The package depends on the Azure.Storage.DataMovement package and can be used in conjuction with other Data Movement sub-packages, such as Azure.Storage.DataMovement.Blobs to transfer data between services. For this release see notes - https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/storage/Azure.Storage.DataMovement.Files.Shares/README.md and https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/storage/Azure.Storage.DataMovement.Files.Shares/CHANGELOG.md
MARS LIFE is a modelling framework for agent-based simulations. It provides the following features: * Agent definitions * Layer definitions * Integration of GIS spatial data like raster-files (*.asc, *.geotiff) and vector formats (*.shp, *.geojson, *.kml, *.gml) * Representations for temporal data with optional spatial reference (spatiotemporal) * Spatial data-structures and agent-environments for movement and explorations * Methods and algorithms for numerical computations for every day use * Result output-pipeline and simulation result persistence For more details how to use MARS, please use the documentation: https://www.mars-group.org/docs/tutorial/intro
Transform financial market price data into technical analysis indicators such as MACD, Stochastic RSI, Average True Range, Parabolic SAR, and more.
ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the JSON connector for ETLBox. It lets you handle structured and semi-structured JSON data, whether working with files or APIs. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the PostgreSQL connector for ETLBox. It supports reading from and writing to PostgreSQL databases for scalable data pipelines. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the CSV connector for ETLBox. It helps you read and write data in CSV format, making it easy to handle flat-file data for import, export, and transformations. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the SQL Server connector for ETLBox. It enables integration with Microsoft SQL Server for handling structured data in ETL workflows. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the MySQL connector for ETLBox. It lets you connect to MySQL databases, handling relational data for ETL tasks and integrations. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the XML connector for ETLBox. It lets you read and write XML data, making it easier to work with hierarchical and structured information. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the Parquet connector for ETLBox. It lets you handle Parquet files, offering an efficient way to process columnar data. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the SQLite connector for ETLBox. It allows you to work with complete SQLite databases, ideal for embedded and local applications. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the Analysis Services connector for ETLBox. It enables you to read and write data to Microsoft SQL Server Analysis Services (SSAS), making it easier to process and manage analytical models. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the MongoDB connector for ETLBox. It helps you work with MongoDB collections, offering support for NoSQL data processing and transformations. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the Couchbase connector for ETLBox. It allows you to integrate with Couchbase databases, providing fast and flexible NoSQL data processing. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the Neo4j connector for ETLBox. It supports graph database integration, enabling you to process and analyze connected data. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/
This is the Tables connector for ETLBox. It supports working with Azure Table Storage, enabling structured data storage and retrieval for cloud-based applications. ETLBox is a complete ETL (Extract, Transform, Load) library and data integration toolbox for .NET. # Build scalable, code-first ETL pipelines for SQL, NoSQL, APIs, and flat files. # Automate data movement, transformation, and synchronization with minimal memory usage. # Ideal for data warehousing, migrations, and big data processing. Simplify your data integration workflow: ETLBox enables efficient, asynchronous data processing by reading from databases, APIs, and file formats like CSV, Excel, and JSON. Transform data dynamically with row-based, batch, or lookup transformations, and read or write from/to multiple destinations in parallel. Key Features: * Stream large datasets efficiently without loading everything into memory * Maximize performance with parallel, task-based data flow execution * Connect to various data sources with built-in connectors or extend with custom components For tutorials, examples, and documentation, visit: https://www.etlbox.net/