Replace 'hub' with 'ingest' in any github url to get a prompt-friendly extract of a codebase

Replace Splunk in your small company with this one weird trick!

IBIS is a workflow creation-engine that abstracts the Hadoop internals of ingesting RDBMS data.

Official NetBox Labs plugin for NetBox for Diode

Python script for ingesting various files into a semantic graph. For text, images, cpp, python, rust, javascript, and PDFs.

This project aims to predict smartphone prices using a combination of batch and stream processing techniques in a Big Data environment. The architecture follows the Lambda Architecture pattern, providing both real-time and batch processing capabilities to users.

Periodically ingest incremental updates (inserts / deletes) into BigQuery using Cloud Composer / Airflow orchestration workflow

Tagbase is a data management system that helps research teams organize and manage in-situ data. It supports different types of data and works with equipment from various manufacturers.

Read-only mirror of https://gitlab.com/sorcero/community/ingestum

Extract Transform and Load unstructured data into the Clarifai's AI platform

Ingest a file in GEDCOM format into MongoDB

A fully interactive tool designed to streamline your GitHub repository prompt generation process and facilitate RAG (Retrieval-Augmented Generation) workflows

LogFlow é uma aplicação ETL (Extração, Transformação e Carregamento) especializada em processamento de logs

Simple python interface for the Fivetran API. Powered by HTTPx.

Exchange collections of files with Large Language Models.

A MongoDb to Elasticsearch ETL pipeline

Automate data ingestion into FiftyOne with Twilio

This project implements a full-stack data engineering solution that connects to the Spotify Web API to extract a user’s recently played tracks, stores the data in a PostgreSQL database, applies transformations using dbt, and delivers actionable insights via Metabase dashboards.

Data ingestor that reads and parses executive orders from wikisource

The aim of this project is automate data ingestion from flat files like CSV and compressed files GZIP into a database like Postgres. The entire setup is automated using Docker and is pretty fast too as multiprocessing is being used.