pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

• UpdatedMar 17, 2025
• Python

The athena adapter plugin for dbt (https://getdbt.com)

• UpdatedFeb 7, 2025
• Python

Examples and custom spark images for working with the spark-on-k8s operator on AWS

• UpdatedFeb 14, 2021
• Dockerfile

🐋 Docker image for AWS Glue Spark/Python

• UpdatedSep 5, 2023
• Dockerfile

Extract, transform, and load data for analytic processing using AWS Glue

• UpdatedMay 2, 2021
• Python

This is a case study showing how to deploy "Wait-for-Callback" using Step Functions

• UpdatedJan 4, 2023
• TypeScript

a toolkit that provides an object-oriented interface for working with parquet datasets on AWS

• UpdatedJun 19, 2023
• Python

Terraform configuration that creates several AWS services, uploads data in S3 and starts the Glue Crawler and Glue Job.

• UpdatedFeb 10, 2022
• Python

Pipeline ETL na AWS

• UpdatedJul 28, 2024
• Python

This repository contains a production-grade ETL (Extract, Transform, Load) pipeline built with AWS Glue and Amazon Redshift. The pipeline processes a raw IMDb movie dataset stored in Amazon S3, applies data quality validation, dynamically routes data based on validation results, and loads it into Amazon Redshift for advanced analytic

• UpdatedJan 24, 2025
• Python

Read the data from a source file using python and then produced that data to a kafka broker using a kafka producer , then consumed the message using a kafka consumer , uploaded the data to a aws s3 bucket then built crawler on top that and then queried that data using aws athena.

• UpdatedAug 18, 2024
• Jupyter Notebook

A pipeline within AWS to capture schema changes in S3 files and to update them in a DB.

• UpdatedNov 30, 2021

ETL using application streaming and creating a Data Lake

• UpdatedApr 7, 2023
• Jupyter Notebook

AWS Kinesis Analytics gather metrics from various computers (cpu, memory), perform aggregation on Kinesis stream data using Kinesis Analytics (with flink) and store the stream data into AWS S3 bucket which is used by Amazon Athena for running various Analytics queries and rending charts using Grafana.

• UpdatedJan 14, 2024
• Java

This workshop is to build a serverless data lake architecture using Amazon Kinesis Firehose for streaming data ingestion, AWS Glue for Data Integration (ETL, Catalogue Management), Amazon S3 for data lake storage, Amazon Athena for SQL big data analytics.

• UpdatedNov 23, 2022
• Jupyter Notebook

IaC (Terraform) of AWS Forecast pipeline using Glue as workflow manager

• UpdatedOct 3, 2024
• Python

This Terraform module automates the setup of AWS Athena to query ALB access and connection logs stored in an S3 bucket.

• UpdatedNov 14, 2024
• HCL

1️⃣ Querying Parquet file from S3 using AwsWrangler. 2️⃣ Querying from Redshift tables using Glue & AwsWrangler

• UpdatedAug 8, 2022
• Jupyter Notebook

The Project aims to establish a robust data pipeline for tracking and analyzing sales performance using various AWS services. The process involves creating a DynamoDB database, implementing Change Data Capture (CDC), utilizing Kinesis streams, and finally, storing and querying the data in Amazon Athena.

• UpdatedFeb 11, 2024
• Python