cargo-crates
Apache Superset
cargo-crates | Apache Superset | |
---|---|---|
3 | 3 | |
1 | 34,745 | |
- | - | |
3.1 | 9.9 | |
about 1 month ago | over 3 years ago | |
Python | Python | |
MIT License | 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.
cargo-crates
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Docker - Magic or Hype?
I've used this benefit in one of my personal side projects (cargo-crates) to have ready-made containers for data extraction purposes. I'm always picking up projects and putting them back down, or shifting which versions of different libraries I have on my laptop, so picking up an old project with specific library dependencies can be really annoying.
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Your default tool for ETL
I went a little crazy and built my own set of data extractors that I can deploy with CDK to ECS.
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Why is it so hard to think of a DE side project idea ?
- Extract data from system. I wear an Oura ring for sleep tracking. I wanted to do my own analysis of the data, so I built a system that could easily allow me to extract the data into S3 so I could query it. https://github.com/dacort/cargo-crates Will anybody find that useful? Maybe...but it's been a heck of a lot of fun and really pushed my Docker skills.
Apache Superset
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Using KeyCloak(OpenID Connect) with Apache SuperSet
The first difference is that after pull request 4565 was merged, you can no longer do:
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Open Source Analytics Stack: Bringing Control, Flexibility, and Data-Privacy to Your Analytics
Open-source BI platforms such as Metabase (website, GitHub) and Apache SuperSet (website, GitHub) are easy to deploy without IT involvement. Metabase lets you build dashboards from the data in your warehouse easily, with no SQL, or, if you have data engineering or science know-how, inside more powerful and flexible notebooks or with SQL itself. Similarly, Apache SuperSet helps businesses explore and visualize data from simple line charts to detailed geospatial charts.
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Ask HN: What low-code “dashboarding“ SaaS would you recommend in 2021?
Check out Superset. https://github.com/apache/incubator-superset
It’s modern, easy to extend. From the same author of apache airflow.
What are some alternatives?
dbt-spark - dbt-spark contains all of the code enabling dbt to work with Apache Spark and Databricks
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
airflow-docker - This is my Apache Airflow Local development setup on Windows 10 WSL2/Mac using docker-compose. It will also include some sample DAGs and workflows.
Grafana - The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
Metabase - The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
cube.js - 📊 Cube — The Semantic Layer for Building Data Applications
grafanalib - Python library for building Grafana dashboards
bokeh - Interactive Data Visualization in the browser, from Python