hudi
Airflow
Our great sponsors
hudi | Airflow | |
---|---|---|
20 | 169 | |
5,053 | 34,397 | |
2.0% | 2.1% | |
9.9 | 10.0 | |
4 days ago | 5 days ago | |
Java | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
hudi
-
Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog
Apache Iceberg is one of the three types of lakehouse, the other two are Apache Hudi and Delta Lake.
-
The "Big Three's" Data Storage Offerings
Structured, Semi-structured and Unstructured can be stored in one single format, a lakehouse storage format like Delta, Iceberg or Hudi (assuming those don't require low-latency SLAs like subsecond).
-
Data-eng related highlights from the latest Thoughtworks Tech Radar
Apache Hudi
- For those of you with Lakehouse Architectures, how do you handle duplicate records?
-
AWS ACID data lakehouse
Try Apache Hudi, it is fully integrated with AWS and offers almost everything that you requested.
-
Data n00b looking for guidance on how to setup data lake/warehouse
the corresponding kafka topics have 30d retention and I intend on having s3 sink connector for long term storage (open to other ideas here too, I noticed theres a hudi connector also)
- apache/hudi: Upserts, Deletes And Incremental Processing on Big Data.
- Big Data file formats
-
How-to-Guide: Contributing to Open Source
Apache Hudi
-
What do you use for Data versioning?
You could have a look at Apache Hudi - especially if you're running your Data Pipelines using Spark or Flink.
Airflow
-
Building in Public: Leveraging Tublian's AI Copilot for My Open Source Contributions
Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.
-
Navigating Week Two: Insights and Experiences from My Tublian Internship Journey
In week Two, I contributed to the Apache Airflow repository.
-
Airflow VS quix-streams - a user suggested alternative
2 projects | 7 Dec 2023
-
Best ETL Tools And Why To Choose
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
-
Simplifying Data Transformation in Redshift: An Approach with DBT and Airflow
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring.
-
Share Your favorite python related software!
AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic!
-
Ask HN: What is the correct way to deal with pipelines?
I agree there are many options in this space. Two others to consider:
- https://airflow.apache.org/
- https://github.com/spotify/luigi
There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file showing up in a directory…
- "Você veio protestar para ter acesso ao código fonte da urnas. O que é o código fonte?" "Não sei" 🤡
- Cómo construir tu propia data platform. From zero to hero.
-
Is it impossible to contribute to open source as a data engineer?
You can try and contribute some new connectors/operators for workflow managers like Airflow or Airbyte
What are some alternatives?
iceberg - Apache Iceberg
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
kudu - Mirror of Apache Kudu
dagster - An orchestration platform for the development, production, and observation of data assets.
Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
debezium - Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
pinot - Apache Pinot - A realtime distributed OLAP datastore
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Dask - Parallel computing with task scheduling