42 packages tagged with “parquet”
Fully managed Apache Parquet implementation.
ParquetSharp is a .NET library for reading and writing Parquet files. It's implemented in C# as a PInvoke wrapper around apache-parquet-cpp to provide high performance and compatibility.
Parquet extension to Cinchoo ETL framework
ParquetSharp.DataFrame is a .NET library for reading and writing Apache Parquet files into/from .NET DataFrames, using ParquetSharp.
Yaml extension to Cinchoo ETL framework
Reader/Writer for GeoParquet files
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/
Enables you to use standard drivers to connect to Parquet objects. Specify your Parquet file location to access the data.
Provides reading and writing Parquet file
Provides Parquet support to the DataPipe platform. Reference this package if you need to read or write Parquet file from a data pipe script
Pansynchro connector to read from Parquet files.
Contains an implementation of the IReadable and IWritable interfaces to access parquet files. Depends on the assemblies TeleScope.Persistence.Abstractions and Parquet.Net.
We present an open-source library, that will help transform AVRO, with nested data, to multiple PARQUET files where each of the nested data elements will be represented as an extension table (separate file)
Seamless integration between Entity Framework Core and DuckDB, providing significant performance improvements for analytical queries with a simple, developer-friendly API.
SQLite extension to Cinchoo ETL framework
An efficient row-oriented dataframe builder and Parquet writer for .NET
Generic mapper for a parquet files.
A .NET standard library for GeoParquet format support (read/write geospatial vector data in Parquet format)
SqlServer extension to Cinchoo ETL framework
A high-performance ADO.NET provider for Parquet files enabling seamless integration with .NET applications. Implements standard DbConnection/DbCommand/DbDataReader patterns for working with Parquet data through familiar ADO.NET abstractions. Features include SQL query support with filtering and projection, parallel reading of row groups, virtual column support, batch processing capabilities, and full async/await compatibility. Ideal for data analytics, ETL operations, and big data processing within the .NET ecosystem.
Parquet source and sink nodes for NPipeline using Parquet.Net - read and write Parquet files with configurable options
.NET tool to extract Tableau usage data and upload to Databricks as Parquet files.
ParquetSharp.Dataset is a .NET library for reading datasets consisting of multiple Parquet files.
A .NET tool for transferring data from SafetyCulture to Databricks.
Core data file processing pipeline for CSV, JSON, Excel, Parquet, and SQLite database ingestion with relationship detection
Strongly-typed access to Parquet files via DuckDB with LINQ query support
A tiny library to simplify working with Parquet Files with Azure Blob Storage using Parquet .Net (parquet-dotnet). Providing easy helpers to load data into class models from Parquet files. This is useful for E-L-T processes whereby you need to load the data into Memory, Sql Server (e.g. Azure SQL), etc. or any other location where there is no built-in support for easily working with Parquet file data.